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undersampling-bagging.ipynb
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| { | |
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| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/kn1kn1/5a7843a58bd3dc9db91aa28862be6fa9/undersampling-bagging.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Classification on imbalanced data with undersampling + bagging\n", | |
| "\n", | |
| "cf. https://www.tensorflow.org/tutorials/structured_data/imbalanced_data" | |
| ], | |
| "metadata": { | |
| "id": "vBjir-dvJit9" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": { | |
| "id": "JM7hDSNClfoK" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import tensorflow as tf\n", | |
| "from tensorflow import keras\n", | |
| "\n", | |
| "import os\n", | |
| "import tempfile\n", | |
| "\n", | |
| "import matplotlib as mpl\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "import numpy as np\n", | |
| "import pandas as pd\n", | |
| "import seaborn as sns\n", | |
| "\n", | |
| "import sklearn\n", | |
| "from sklearn.metrics import confusion_matrix\n", | |
| "from sklearn.model_selection import train_test_split\n", | |
| "from sklearn.preprocessing import StandardScaler" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": { | |
| "id": "c8o1FHzD-_y_" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "mpl.rcParams['figure.figsize'] = (12, 10)\n", | |
| "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import random\n", | |
| "import numpy as np\n", | |
| "import tensorflow as tf\n", | |
| "\n", | |
| "seed = 42\n", | |
| "random.seed(seed)\n", | |
| "np.random.seed(seed)\n", | |
| "tf.random.set_seed(seed)" | |
| ], | |
| "metadata": { | |
| "id": "SZRVGoVIJsy8" | |
| }, | |
| "execution_count": 3, | |
| "outputs": [] | |
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| "execution_count": 4, | |
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| "id": "pR_SnbMArXr7", | |
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| "base_uri": "https://localhost:8080/", | |
| "height": 300 | |
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| "outputId": "242a50fb-df59-4066-bb7f-af8f2b409dfa" | |
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| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| " Time V1 V2 V3 V4 V5 V6 V7 \\\n", | |
| "0 0.0 -1.359807 -0.072781 2.536347 1.378155 -0.338321 0.462388 0.239599 \n", | |
| "1 0.0 1.191857 0.266151 0.166480 0.448154 0.060018 -0.082361 -0.078803 \n", | |
| "2 1.0 -1.358354 -1.340163 1.773209 0.379780 -0.503198 1.800499 0.791461 \n", | |
| "3 1.0 -0.966272 -0.185226 1.792993 -0.863291 -0.010309 1.247203 0.237609 \n", | |
| "4 2.0 -1.158233 0.877737 1.548718 0.403034 -0.407193 0.095921 0.592941 \n", | |
| "\n", | |
| " V8 V9 ... V21 V22 V23 V24 V25 \\\n", | |
| "0 0.098698 0.363787 ... -0.018307 0.277838 -0.110474 0.066928 0.128539 \n", | |
| "1 0.085102 -0.255425 ... -0.225775 -0.638672 0.101288 -0.339846 0.167170 \n", | |
| "2 0.247676 -1.514654 ... 0.247998 0.771679 0.909412 -0.689281 -0.327642 \n", | |
| "3 0.377436 -1.387024 ... -0.108300 0.005274 -0.190321 -1.175575 0.647376 \n", | |
| "4 -0.270533 0.817739 ... -0.009431 0.798278 -0.137458 0.141267 -0.206010 \n", | |
| "\n", | |
| " V26 V27 V28 Amount Class \n", | |
| "0 -0.189115 0.133558 -0.021053 149.62 0 \n", | |
| "1 0.125895 -0.008983 0.014724 2.69 0 \n", | |
| "2 -0.139097 -0.055353 -0.059752 378.66 0 \n", | |
| "3 -0.221929 0.062723 0.061458 123.50 0 \n", | |
| "4 0.502292 0.219422 0.215153 69.99 0 \n", | |
| "\n", | |
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| " <td>-1.359807</td>\n", | |
| " <td>-0.072781</td>\n", | |
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| " <th>1</th>\n", | |
| " <td>0.0</td>\n", | |
| " <td>1.191857</td>\n", | |
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| " <td>0.125895</td>\n", | |
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| " <td>0.014724</td>\n", | |
| " <td>2.69</td>\n", | |
| " <td>0</td>\n", | |
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| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>1.0</td>\n", | |
| " <td>-1.358354</td>\n", | |
| " <td>-1.340163</td>\n", | |
| " <td>1.773209</td>\n", | |
| " <td>0.379780</td>\n", | |
| " <td>-0.503198</td>\n", | |
| " <td>1.800499</td>\n", | |
| " <td>0.791461</td>\n", | |
| " <td>0.247676</td>\n", | |
| " <td>-1.514654</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0.247998</td>\n", | |
| " <td>0.771679</td>\n", | |
| " <td>0.909412</td>\n", | |
| " <td>-0.689281</td>\n", | |
| " <td>-0.327642</td>\n", | |
| " <td>-0.139097</td>\n", | |
| " <td>-0.055353</td>\n", | |
| " <td>-0.059752</td>\n", | |
| " <td>378.66</td>\n", | |
| " <td>0</td>\n", | |
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| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>1.0</td>\n", | |
| " <td>-0.966272</td>\n", | |
| " <td>-0.185226</td>\n", | |
| " <td>1.792993</td>\n", | |
| " <td>-0.863291</td>\n", | |
| " <td>-0.010309</td>\n", | |
| " <td>1.247203</td>\n", | |
| " <td>0.237609</td>\n", | |
| " <td>0.377436</td>\n", | |
| " <td>-1.387024</td>\n", | |
| " <td>...</td>\n", | |
| " <td>-0.108300</td>\n", | |
| " <td>0.005274</td>\n", | |
| " <td>-0.190321</td>\n", | |
| " <td>-1.175575</td>\n", | |
| " <td>0.647376</td>\n", | |
| " <td>-0.221929</td>\n", | |
| " <td>0.062723</td>\n", | |
| " <td>0.061458</td>\n", | |
| " <td>123.50</td>\n", | |
| " <td>0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>2.0</td>\n", | |
| " <td>-1.158233</td>\n", | |
| " <td>0.877737</td>\n", | |
| " <td>1.548718</td>\n", | |
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| " <td>0.502292</td>\n", | |
| " <td>0.219422</td>\n", | |
| " <td>0.215153</td>\n", | |
| " <td>69.99</td>\n", | |
| " <td>0</td>\n", | |
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| "metadata": {}, | |
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| "source": [ | |
| "file = tf.keras.utils\n", | |
| "raw_df = pd.read_csv('https://storage.googleapis.com/download.tensorflow.org/data/creditcard.csv')\n", | |
| "raw_df.head()" | |
| ] | |
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| " Time V1 V2 V3 V4 \\\n", | |
| "count 284807.000000 2.848070e+05 2.848070e+05 2.848070e+05 2.848070e+05 \n", | |
| "mean 94813.859575 1.168375e-15 3.416908e-16 -1.379537e-15 2.074095e-15 \n", | |
| "std 47488.145955 1.958696e+00 1.651309e+00 1.516255e+00 1.415869e+00 \n", | |
| "min 0.000000 -5.640751e+01 -7.271573e+01 -4.832559e+01 -5.683171e+00 \n", | |
| "25% 54201.500000 -9.203734e-01 -5.985499e-01 -8.903648e-01 -8.486401e-01 \n", | |
| "50% 84692.000000 1.810880e-02 6.548556e-02 1.798463e-01 -1.984653e-02 \n", | |
| "75% 139320.500000 1.315642e+00 8.037239e-01 1.027196e+00 7.433413e-01 \n", | |
| "max 172792.000000 2.454930e+00 2.205773e+01 9.382558e+00 1.687534e+01 \n", | |
| "\n", | |
| " V5 V26 V27 V28 Amount \\\n", | |
| "count 2.848070e+05 2.848070e+05 2.848070e+05 2.848070e+05 284807.000000 \n", | |
| "mean 9.604066e-16 1.683437e-15 -3.660091e-16 -1.227390e-16 88.349619 \n", | |
| "std 1.380247e+00 4.822270e-01 4.036325e-01 3.300833e-01 250.120109 \n", | |
| "min -1.137433e+02 -2.604551e+00 -2.256568e+01 -1.543008e+01 0.000000 \n", | |
| "25% -6.915971e-01 -3.269839e-01 -7.083953e-02 -5.295979e-02 5.600000 \n", | |
| "50% -5.433583e-02 -5.213911e-02 1.342146e-03 1.124383e-02 22.000000 \n", | |
| "75% 6.119264e-01 2.409522e-01 9.104512e-02 7.827995e-02 77.165000 \n", | |
| "max 3.480167e+01 3.517346e+00 3.161220e+01 3.384781e+01 25691.160000 \n", | |
| "\n", | |
| " Class \n", | |
| "count 284807.000000 \n", | |
| "mean 0.001727 \n", | |
| "std 0.041527 \n", | |
| "min 0.000000 \n", | |
| "25% 0.000000 \n", | |
| "50% 0.000000 \n", | |
| "75% 0.000000 \n", | |
| "max 1.000000 " | |
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| " <th>V28</th>\n", | |
| " <th>Amount</th>\n", | |
| " <th>Class</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>count</th>\n", | |
| " <td>284807.000000</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>2.848070e+05</td>\n", | |
| " <td>284807.000000</td>\n", | |
| " <td>284807.000000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>mean</th>\n", | |
| " <td>94813.859575</td>\n", | |
| " <td>1.168375e-15</td>\n", | |
| " <td>3.416908e-16</td>\n", | |
| " <td>-1.379537e-15</td>\n", | |
| " <td>2.074095e-15</td>\n", | |
| " <td>9.604066e-16</td>\n", | |
| " <td>1.683437e-15</td>\n", | |
| " <td>-3.660091e-16</td>\n", | |
| " <td>-1.227390e-16</td>\n", | |
| " <td>88.349619</td>\n", | |
| " <td>0.001727</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>std</th>\n", | |
| " <td>47488.145955</td>\n", | |
| " <td>1.958696e+00</td>\n", | |
| " <td>1.651309e+00</td>\n", | |
| " <td>1.516255e+00</td>\n", | |
| " <td>1.415869e+00</td>\n", | |
| " <td>1.380247e+00</td>\n", | |
| " <td>4.822270e-01</td>\n", | |
| " <td>4.036325e-01</td>\n", | |
| " <td>3.300833e-01</td>\n", | |
| " <td>250.120109</td>\n", | |
| " <td>0.041527</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>min</th>\n", | |
| " <td>0.000000</td>\n", | |
| " <td>-5.640751e+01</td>\n", | |
| " <td>-7.271573e+01</td>\n", | |
| " <td>-4.832559e+01</td>\n", | |
| " <td>-5.683171e+00</td>\n", | |
| " <td>-1.137433e+02</td>\n", | |
| " <td>-2.604551e+00</td>\n", | |
| " <td>-2.256568e+01</td>\n", | |
| " <td>-1.543008e+01</td>\n", | |
| " <td>0.000000</td>\n", | |
| " <td>0.000000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25%</th>\n", | |
| " <td>54201.500000</td>\n", | |
| " <td>-9.203734e-01</td>\n", | |
| " <td>-5.985499e-01</td>\n", | |
| " <td>-8.903648e-01</td>\n", | |
| " <td>-8.486401e-01</td>\n", | |
| " <td>-6.915971e-01</td>\n", | |
| " <td>-3.269839e-01</td>\n", | |
| " <td>-7.083953e-02</td>\n", | |
| " <td>-5.295979e-02</td>\n", | |
| " <td>5.600000</td>\n", | |
| " <td>0.000000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>50%</th>\n", | |
| " <td>84692.000000</td>\n", | |
| " <td>1.810880e-02</td>\n", | |
| " <td>6.548556e-02</td>\n", | |
| " <td>1.798463e-01</td>\n", | |
| " <td>-1.984653e-02</td>\n", | |
| " <td>-5.433583e-02</td>\n", | |
| " <td>-5.213911e-02</td>\n", | |
| " <td>1.342146e-03</td>\n", | |
| " <td>1.124383e-02</td>\n", | |
| " <td>22.000000</td>\n", | |
| " <td>0.000000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>75%</th>\n", | |
| " <td>139320.500000</td>\n", | |
| " <td>1.315642e+00</td>\n", | |
| " <td>8.037239e-01</td>\n", | |
| " <td>1.027196e+00</td>\n", | |
| " <td>7.433413e-01</td>\n", | |
| " <td>6.119264e-01</td>\n", | |
| " <td>2.409522e-01</td>\n", | |
| " <td>9.104512e-02</td>\n", | |
| " <td>7.827995e-02</td>\n", | |
| " <td>77.165000</td>\n", | |
| " <td>0.000000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>max</th>\n", | |
| " <td>172792.000000</td>\n", | |
| " <td>2.454930e+00</td>\n", | |
| " <td>2.205773e+01</td>\n", | |
| " <td>9.382558e+00</td>\n", | |
| " <td>1.687534e+01</td>\n", | |
| " <td>3.480167e+01</td>\n", | |
| " <td>3.517346e+00</td>\n", | |
| " <td>3.161220e+01</td>\n", | |
| " <td>3.384781e+01</td>\n", | |
| " <td>25691.160000</td>\n", | |
| " <td>1.000000</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</div>\n", | |
| " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-901d4670-e55f-4ba4-addd-5da739f5e545')\"\n", | |
| " title=\"Convert this dataframe to an interactive table.\"\n", | |
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| " \n", | |
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| " </button>\n", | |
| " \n", | |
| " <style>\n", | |
| " .colab-df-container {\n", | |
| " display:flex;\n", | |
| " flex-wrap:wrap;\n", | |
| " gap: 12px;\n", | |
| " }\n", | |
| "\n", | |
| " .colab-df-convert {\n", | |
| " background-color: #E8F0FE;\n", | |
| " border: none;\n", | |
| " border-radius: 50%;\n", | |
| " cursor: pointer;\n", | |
| " display: none;\n", | |
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| " height: 32px;\n", | |
| " padding: 0 0 0 0;\n", | |
| " width: 32px;\n", | |
| " }\n", | |
| "\n", | |
| " .colab-df-convert:hover {\n", | |
| " background-color: #E2EBFA;\n", | |
| " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n", | |
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| " }\n", | |
| "\n", | |
| " [theme=dark] .colab-df-convert {\n", | |
| " background-color: #3B4455;\n", | |
| " fill: #D2E3FC;\n", | |
| " }\n", | |
| "\n", | |
| " [theme=dark] .colab-df-convert:hover {\n", | |
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| " </style>\n", | |
| "\n", | |
| " <script>\n", | |
| " const buttonEl =\n", | |
| " document.querySelector('#df-901d4670-e55f-4ba4-addd-5da739f5e545 button.colab-df-convert');\n", | |
| " buttonEl.style.display =\n", | |
| " google.colab.kernel.accessAllowed ? 'block' : 'none';\n", | |
| "\n", | |
| " async function convertToInteractive(key) {\n", | |
| " const element = document.querySelector('#df-901d4670-e55f-4ba4-addd-5da739f5e545');\n", | |
| " const dataTable =\n", | |
| " await google.colab.kernel.invokeFunction('convertToInteractive',\n", | |
| " [key], {});\n", | |
| " if (!dataTable) return;\n", | |
| "\n", | |
| " const docLinkHtml = 'Like what you see? Visit the ' +\n", | |
| " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n", | |
| " + ' to learn more about interactive tables.';\n", | |
| " element.innerHTML = '';\n", | |
| " dataTable['output_type'] = 'display_data';\n", | |
| " await google.colab.output.renderOutput(dataTable, element);\n", | |
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| " element.appendChild(docLink);\n", | |
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| " </div>\n", | |
| " " | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 5 | |
| } | |
| ], | |
| "source": [ | |
| "raw_df[['Time', 'V1', 'V2', 'V3', 'V4', 'V5', 'V26', 'V27', 'V28', 'Amount', 'Class']].describe()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": { | |
| "id": "HCJFrtuY2iLF", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "bc849d5b-59d0-4c3a-d0e8-d1673df6c6fa" | |
| }, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Examples:\n", | |
| " Total: 284807\n", | |
| " Positive: 492 (0.17% of total)\n", | |
| "\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "neg, pos = np.bincount(raw_df['Class'])\n", | |
| "total = neg + pos\n", | |
| "print('Examples:\\n Total: {}\\n Positive: {} ({:.2f}% of total)\\n'.format(\n", | |
| " total, pos, 100 * pos / total))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "metadata": { | |
| "id": "Ef42jTuxEjnj" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "cleaned_df = raw_df.copy()\n", | |
| "\n", | |
| "# You don't want the `Time` column.\n", | |
| "cleaned_df.pop('Time')\n", | |
| "\n", | |
| "# The `Amount` column covers a huge range. Convert to log-space.\n", | |
| "eps = 0.001 # 0 => 0.1¢\n", | |
| "cleaned_df['Log Amount'] = np.log(cleaned_df.pop('Amount')+eps)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": { | |
| "id": "xfxhKg7Yr1-b" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "# Use a utility from sklearn to split and shuffle your dataset.\n", | |
| "train_df, test_df = train_test_split(cleaned_df, test_size=0.2, random_state=42)\n", | |
| "train_df, val_df = train_test_split(train_df, test_size=0.2, random_state=42)\n", | |
| "\n", | |
| "# Form np arrays of labels and features.\n", | |
| "train_labels = np.array(train_df.pop('Class'))\n", | |
| "bool_train_labels = train_labels != 0\n", | |
| "val_labels = np.array(val_df.pop('Class'))\n", | |
| "test_labels = np.array(test_df.pop('Class'))\n", | |
| "\n", | |
| "train_features = np.array(train_df)\n", | |
| "val_features = np.array(val_df)\n", | |
| "test_features = np.array(test_df)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": { | |
| "id": "IO-qEUmJ5JQg", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "e71a1867-ad78-4f37-d186-b8ceee7313dd" | |
| }, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Training labels shape: (182276,)\n", | |
| "Validation labels shape: (45569,)\n", | |
| "Test labels shape: (56962,)\n", | |
| "Training features shape: (182276, 29)\n", | |
| "Validation features shape: (45569, 29)\n", | |
| "Test features shape: (56962, 29)\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "scaler = StandardScaler()\n", | |
| "train_features = scaler.fit_transform(train_features)\n", | |
| "\n", | |
| "val_features = scaler.transform(val_features)\n", | |
| "test_features = scaler.transform(test_features)\n", | |
| "\n", | |
| "train_features = np.clip(train_features, -5, 5)\n", | |
| "val_features = np.clip(val_features, -5, 5)\n", | |
| "test_features = np.clip(test_features, -5, 5)\n", | |
| "\n", | |
| "\n", | |
| "print('Training labels shape:', train_labels.shape)\n", | |
| "print('Validation labels shape:', val_labels.shape)\n", | |
| "print('Test labels shape:', test_labels.shape)\n", | |
| "\n", | |
| "print('Training features shape:', train_features.shape)\n", | |
| "print('Validation features shape:', val_features.shape)\n", | |
| "print('Test features shape:', test_features.shape)\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": { | |
| "id": "MVWBGfADwbWI" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def plot_cm(labels, predictions, p=0.5):\n", | |
| " cm = confusion_matrix(labels, predictions > p)\n", | |
| " plt.figure(figsize=(5,5))\n", | |
| " sns.heatmap(cm, annot=True, fmt=\"d\")\n", | |
| " plt.title('Confusion matrix @{:.2f}'.format(p))\n", | |
| " plt.ylabel('Actual label')\n", | |
| " plt.xlabel('Predicted label')\n", | |
| "\n", | |
| " print('Legitimate Transactions Detected (True Negatives): ', cm[0][0])\n", | |
| " print('Legitimate Transactions Incorrectly Detected (False Positives): ', cm[0][1])\n", | |
| " print('Fraudulent Transactions Missed (False Negatives): ', cm[1][0])\n", | |
| " print('Fraudulent Transactions Detected (True Positives): ', cm[1][1])\n", | |
| " print('Total Fraudulent Transactions: ', np.sum(cm[1]))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "id": "lhaxsLSvANF9" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def plot_roc(name, labels, predictions, **kwargs):\n", | |
| " fp, tp, _ = sklearn.metrics.roc_curve(labels, predictions)\n", | |
| "\n", | |
| " plt.plot(100*fp, 100*tp, label=name, linewidth=2, **kwargs)\n", | |
| " plt.xlabel('False positives [%]')\n", | |
| " plt.ylabel('True positives [%]')\n", | |
| " plt.xlim([-0.5,20])\n", | |
| " plt.ylim([80,100.5])\n", | |
| " plt.grid(True)\n", | |
| " ax = plt.gca()\n", | |
| " ax.set_aspect('equal')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": { | |
| "id": "XV6JSlFGEqGI" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def plot_prc(name, labels, predictions, **kwargs):\n", | |
| " precision, recall, _ = sklearn.metrics.precision_recall_curve(labels, predictions)\n", | |
| "\n", | |
| " plt.plot(precision, recall, label=name, linewidth=2, **kwargs)\n", | |
| " plt.xlabel('Precision')\n", | |
| " plt.ylabel('Recall')\n", | |
| " plt.grid(True)\n", | |
| " ax = plt.gca()\n", | |
| " ax.set_aspect('equal')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "undersamplingをしない場合の性能" | |
| ], | |
| "metadata": { | |
| "id": "qHLmyUDo9Luq" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from imblearn.pipeline import Pipeline\n", | |
| "from imblearn.under_sampling import RandomUnderSampler\n", | |
| "from sklearn.ensemble import RandomForestClassifier\n", | |
| "\n", | |
| "neg, pos = np.bincount(train_labels)\n", | |
| "total = neg + pos\n", | |
| "print('Examples:\\n Total: {}\\n Positive: {} ({:.2f}% of total)\\n'.format(\n", | |
| " total, pos, 100 * pos / total))\n", | |
| "train_f_count = neg\n", | |
| "train_t_count = pos\n", | |
| "\n", | |
| "classifier = RandomForestClassifier(\n", | |
| " random_state = 42,\n", | |
| " n_jobs = -1\n", | |
| ")\n", | |
| "\n", | |
| "classifier.fit(train_df, train_labels)" | |
| ], | |
| "metadata": { | |
| "id": "qg5RnlTH7oqt", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "462ce387-7bc5-49c4-cd77-ca2700758b7e" | |
| }, | |
| "execution_count": 13, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Examples:\n", | |
| " Total: 182276\n", | |
| " Positive: 330 (0.18% of total)\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "RandomForestClassifier(n_jobs=-1, random_state=42)" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 13 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "train_predictions_undersampled = classifier.predict_proba(train_df)\n", | |
| "test_predictions_undersampled = classifier.predict_proba(test_df)\n", | |
| "train_predictions_undersampled_proba_t = train_predictions_undersampled.T[1]\n", | |
| "test_predictions_undersampled_proba_t = test_predictions_undersampled.T[1]" | |
| ], | |
| "metadata": { | |
| "id": "h_UODutJ_s_r" | |
| }, | |
| "execution_count": 14, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_cm(test_labels, test_predictions_undersampled_proba_t)" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 439 | |
| }, | |
| "id": "cABztjTAHf1V", | |
| "outputId": "f345a3a3-7c16-435d-e5a5-d771d89fda27" | |
| }, | |
| "execution_count": 15, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Legitimate Transactions Detected (True Negatives): 56860\n", | |
| "Legitimate Transactions Incorrectly Detected (False Positives): 4\n", | |
| "Fraudulent Transactions Missed (False Negatives): 22\n", | |
| "Fraudulent Transactions Detected (True Positives): 76\n", | |
| "Total Fraudulent Transactions: 98\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 360x360 with 2 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 16, | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 606 | |
| }, | |
| "outputId": "ef0b207f-3f79-486f-ef1d-39fa4dd5a591", | |
| "id": "2jeHc_7tC6VQ" | |
| }, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ], | |
| "source": [ | |
| "plot_roc(\"Train base (NOT Undersampled)\", train_labels, train_predictions_undersampled_proba_t, color=colors[0])\n", | |
| "plot_roc(\"Test base (NOT Undersampled)\", test_labels, test_predictions_undersampled_proba_t, color=colors[0], linestyle='--')\n", | |
| "\n", | |
| "plt.legend(loc='lower right');" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_prc(\"Train base (NOT Undersampled)\", train_labels, train_predictions_undersampled_proba_t, color=colors[0])\n", | |
| "plot_prc(\"Test base (NOT Undersampled)\", test_labels, test_predictions_undersampled_proba_t, color=colors[0], linestyle='--')\n", | |
| "\n", | |
| "plt.legend(loc='lower right');" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 606 | |
| }, | |
| "id": "8_In-YxB_97c", | |
| "outputId": "ca73e8b2-5695-42d7-b0f9-44a8e2c66fed" | |
| }, | |
| "execution_count": 17, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from sklearn.metrics import confusion_matrix, make_scorer\n", | |
| "\n", | |
| "def cm_tp(y, y_pred, **kwargs):\n", | |
| " tn, fp, fn, tp = confusion_matrix(y, y_pred).ravel()\n", | |
| " return tp\n", | |
| "def cm_fp(y, y_pred, **kwargs):\n", | |
| " # cm = confusion_matrix(y, y_pred)\n", | |
| " tn, fp, fn, tp = confusion_matrix(y, y_pred).ravel()\n", | |
| " return fp\n", | |
| "def cm_tn(y, y_pred, **kwargs):\n", | |
| " tn, fp, fn, tp = confusion_matrix(y, y_pred).ravel()\n", | |
| " return tn\n", | |
| "def cm_fn(y, y_pred, **kwargs):\n", | |
| " tn, fp, fn, tp = confusion_matrix(y, y_pred).ravel()\n", | |
| " return fn\n", | |
| "\n", | |
| "tp_scorer = make_scorer(cm_tp)\n", | |
| "fp_scorer = make_scorer(cm_fp)\n", | |
| "tn_scorer = make_scorer(cm_tn)\n", | |
| "fn_scorer = make_scorer(cm_fn)\n", | |
| "\n", | |
| "scoring = {\n", | |
| " \"f1\": \"f1\", \n", | |
| " \"precision\": \"precision\",\n", | |
| " \"recall\": \"recall\",\n", | |
| " \"tp\": tp_scorer,\n", | |
| " \"fp\": fp_scorer,\n", | |
| " \"tn\": tn_scorer,\n", | |
| " \"fn\": fn_scorer,\n", | |
| "}" | |
| ], | |
| "metadata": { | |
| "id": "dx4mTr7JTNTI" | |
| }, | |
| "execution_count": 18, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "undersampling実施。\n", | |
| "\n", | |
| "負例をどのくらい減らすかのratioを1〜0.01でグリッドサーチしてみる。" | |
| ], | |
| "metadata": { | |
| "id": "R4EWvpRLbSrH" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# そこそこ時間が掛かるので、一度試したらコメントアウトしたほうが良い\n", | |
| "\n", | |
| "from imblearn.under_sampling import RandomUnderSampler\n", | |
| "from sklearn.ensemble import RandomForestClassifier\n", | |
| "from sklearn.model_selection import GridSearchCV\n", | |
| "\n", | |
| "# ratios = [1, 1.45, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16, 20]\n", | |
| "ratios = [1, 0.75, 0.5, 0.25, 0.125, 0.05, 0.01]\n", | |
| "parameters = {'n_estimators': [100]}\n", | |
| "\n", | |
| "\n", | |
| "neg, pos = np.bincount(train_labels)\n", | |
| "total = neg + pos\n", | |
| "print('Examples:\\n Total: {}\\n Positive: {} ({:.2f}% of total)\\n'.format(\n", | |
| " total, pos, 100 * pos / total))\n", | |
| "train_f_count = neg\n", | |
| "train_t_count = pos\n", | |
| "\n", | |
| "\n", | |
| "rus_results = dict()\n", | |
| "for n, ratio in enumerate(ratios):\n", | |
| " under_sampling_rate = ratio\n", | |
| " sampler = RandomUnderSampler(\n", | |
| " sampling_strategy = {0 : int(train_f_count * under_sampling_rate), 1 : train_t_count}, \n", | |
| " random_state = 42\n", | |
| " )\n", | |
| "\n", | |
| " # sampler = RandomUnderSampler(\n", | |
| " # sampling_strategy = {0 : int(train_t_count * under_sampling_rate), 1 : train_t_count}, \n", | |
| " # random_state = 42\n", | |
| " # )\n", | |
| "\n", | |
| " train_res_df, train_res_labels = sampler.fit_resample(train_df, train_labels)\n", | |
| "\n", | |
| " model = RandomForestClassifier(\n", | |
| " random_state = 42,\n", | |
| " n_jobs = -1\n", | |
| " )\n", | |
| " \n", | |
| " tree_grid_search = GridSearchCV(model, param_grid=parameters, verbose=2, n_jobs=-1, cv=5, return_train_score=True, scoring = scoring, refit=False)\n", | |
| " tree_grid_search.fit(train_res_df, train_res_labels)\n", | |
| " rus_results[ratio] = tree_grid_search\n" | |
| ], | |
| "metadata": { | |
| "id": "md47vbndCASr", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "8db108a9-54c0-4431-b670-034b53f3e9b8" | |
| }, | |
| "execution_count": 19, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Examples:\n", | |
| " Total: 182276\n", | |
| " Positive: 330 (0.18% of total)\n", | |
| "\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "def plot_results(result_dict, ratios, metrics, param = 'class_ratio', name = 'undersampling rate'):\n", | |
| " for n, metric in enumerate(metrics):\n", | |
| " train_scores = np.array([])\n", | |
| " test_scores = np.array([])\n", | |
| " for rr, ratio in enumerate(ratios):\n", | |
| " model = result_dict[ratio]\n", | |
| " train_score = model.cv_results_['mean_train_%s' % metric]\n", | |
| " train_scores = np.append(train_scores, train_score)\n", | |
| " test_score = model.cv_results_['mean_test_%s' % metric]\n", | |
| " test_scores = np.append(test_scores, test_score)\n", | |
| "\n", | |
| " param_values = ratios\n", | |
| " plt.subplot(2, 2, n+1)\n", | |
| " plt.plot(param_values, train_scores, 'o', color=colors[0], linestyle=\"-\", label = 'train')\n", | |
| " plt.plot(param_values, test_scores, 'o', color=colors[1], linestyle=\"--\", label = 'test')\n", | |
| "\n", | |
| " plt.xlabel(name)\n", | |
| " plt.ylabel(metric)\n", | |
| " if metric in [\"precision\"]:\n", | |
| " plt.ylim([0.7, 1.05])\n", | |
| " elif metric in [\"f1\", \"recall\"]:\n", | |
| " plt.ylim([0.7, 1.05])\n", | |
| "\n", | |
| " plt.legend()\n", | |
| " plt.tight_layout(pad = 4)\n", | |
| " \n", | |
| "plot_results(rus_results, ratios, [\"f1\", \"precision\", \"recall\",])" | |
| ], | |
| "metadata": { | |
| "id": "cUrpCS8rT1mK", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 671 | |
| }, | |
| "outputId": "50f5b409-4f8d-4479-9aa6-7bc69c4283f9" | |
| }, | |
| "execution_count": 20, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 3 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_results(rus_results, ratios, [\"tn\", \"fp\", \"fn\", \"tp\",])" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 671 | |
| }, | |
| "id": "Z_GmRs2nKSUy", | |
| "outputId": "aad01a0d-ab0c-4a61-8927-b8fef3098906" | |
| }, | |
| "execution_count": 21, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 4 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "ratioが小さくなるほど、f1, precision, recallが向上する傾向にあった。\n", | |
| "\n", | |
| "訓練データの負例181,946個の0.01倍は1,819個で、これは正例330個の5.51倍に相当するので、1から10のratioで再度グリッドサーチする。" | |
| ], | |
| "metadata": { | |
| "id": "Zh4FCpQKVtz7" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from imblearn.under_sampling import RandomUnderSampler\n", | |
| "from sklearn.ensemble import RandomForestClassifier\n", | |
| "from sklearn.model_selection import GridSearchCV\n", | |
| "\n", | |
| "ratios = [1, 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10]\n", | |
| "# ratios = [1, 0.75, 0.5, 0.25, 0.125, 0.05, 0.01]\n", | |
| "parameters = {'n_estimators': [100]}\n", | |
| "\n", | |
| "\n", | |
| "neg, pos = np.bincount(train_labels)\n", | |
| "total = neg + pos\n", | |
| "print('Examples:\\n Total: {}\\n Positive: {} ({:.2f}% of total)\\n'.format(\n", | |
| " total, pos, 100 * pos / total))\n", | |
| "train_f_count = neg\n", | |
| "train_t_count = pos\n", | |
| "\n", | |
| "\n", | |
| "rus_results = dict()\n", | |
| "for n, ratio in enumerate(ratios):\n", | |
| " under_sampling_rate = ratio\n", | |
| " # sampler = RandomUnderSampler(\n", | |
| " # sampling_strategy = {0 : int(train_f_count * under_sampling_rate), 1 : train_t_count}, \n", | |
| " # random_state = 42\n", | |
| " # )\n", | |
| "\n", | |
| " sampler = RandomUnderSampler(\n", | |
| " sampling_strategy = {0 : int(train_t_count * under_sampling_rate), 1 : train_t_count}, \n", | |
| " random_state = 42\n", | |
| " )\n", | |
| "\n", | |
| " train_res_df, train_res_labels = sampler.fit_resample(train_df, train_labels)\n", | |
| "\n", | |
| " model = RandomForestClassifier(\n", | |
| " random_state = 42,\n", | |
| " n_jobs = -1\n", | |
| " )\n", | |
| " \n", | |
| " tree_grid_search = GridSearchCV(model, param_grid=parameters, verbose=2, n_jobs=-1, cv=5, return_train_score=True, scoring = scoring, refit=False)\n", | |
| " tree_grid_search.fit(train_res_df, train_res_labels)\n", | |
| " rus_results[ratio] = tree_grid_search\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "oJLMugwQUrS9", | |
| "outputId": "ca91f2ce-c146-447a-bca3-3a7bf08692f1" | |
| }, | |
| "execution_count": 22, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Examples:\n", | |
| " Total: 182276\n", | |
| " Positive: 330 (0.18% of total)\n", | |
| "\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n", | |
| "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "def plot_results(result_dict, ratios, metrics, param = 'class_ratio', name = 'Class Ratio\\n(False label count / True label count)'):\n", | |
| " for n, metric in enumerate(metrics):\n", | |
| " train_scores = np.array([])\n", | |
| " test_scores = np.array([])\n", | |
| " for rr, ratio in enumerate(ratios):\n", | |
| " model = result_dict[ratio]\n", | |
| " train_score = model.cv_results_['mean_train_%s' % metric]\n", | |
| " train_scores = np.append(train_scores, train_score)\n", | |
| " test_score = model.cv_results_['mean_test_%s' % metric]\n", | |
| " test_scores = np.append(test_scores, test_score)\n", | |
| "\n", | |
| " param_values = ratios\n", | |
| " plt.subplot(2, 2, n+1)\n", | |
| " plt.plot(param_values, train_scores, 'o', color=colors[0], linestyle=\"-\", label = 'train')\n", | |
| " plt.plot(param_values, test_scores, 'o', color=colors[1], linestyle=\"--\", label = 'test')\n", | |
| "\n", | |
| " plt.xlabel(name)\n", | |
| " plt.ylabel(metric)\n", | |
| " if metric in [\"precision\"]:\n", | |
| " plt.ylim([0.95, 1.05])\n", | |
| " elif metric in [\"f1\", \"recall\"]:\n", | |
| " plt.ylim([0.8, 1.05])\n", | |
| "\n", | |
| " plt.legend()\n", | |
| " plt.tight_layout(pad = 4)\n", | |
| " \n", | |
| "plot_results(rus_results, ratios, [\"f1\", \"precision\", \"recall\",])" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 671 | |
| }, | |
| "id": "y_-MDkHeWx-d", | |
| "outputId": "d7c31cb9-1e14-40ea-ac3c-89d257f2273b" | |
| }, | |
| "execution_count": 23, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 3 Axes>" | |
| ], | |
| "image/png": 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k4nMohsyIw8woLMinsCCfvTvsfgxHjZ/BijUbtyvvUVLE01efsPsn3gWZ8OeRCTGIiIikQmxjPMxsEqHlogvwPmGmqgIAd78tmk73D4SB4xuAi919bnTsV4H/iU71S3f/y46upz63eybpWa1EGtrdMR7SOI3xSB3VNyIiTUtkjIe7n7OD7Q58u4ltE4GJccQljTtjSA/9mJOMojv9IiIiLUtWDy4XkZZNCbGIiEjLsXMjLEVERERERPaAEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REREREYmdEg8REclqZjbRzFaa2aImtpuZ3WRmS81soZkdEpUPNrNnzWxxVP7l9EYuIpJblHiIiEi2uwMY0cz2U4C+0WM0cGtUvgG4wN0Pio6/0cxKYoxTRCSntUo6ABERkT3h7rPNrHczu5wO3OXuDjxnZiVmtq+7v17vHCvMbCXQFVgTa8AiIjlKLR4iItLS9QCW13tfHpVtZWZDgdbAsjTGJSKSU5R4iIhITjOzfYG/Ahe7e00T+4w2s7lmNnfVqlXpDVBEpIVQ4iEiIi1dBdCz3vvSqAwz2wt4CPiRuz/X1AncfYK7l7l7WdeuXWMNVkSkpVLiISIiLd1U4IJodqsjgLXu/p6ZtQbuJ4z/mJJsiCIiLZ8Gl4uISFYzs0nA8UAXMysHfgoUALj7bcB0YCSwlDCT1cXRoaOAY4HOZnZRVHaRu7+YtuBFRHKIEg8REclq7n7ODrY78O1Gyu8G7o4rLhER2Za6WomIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOyUeIiIiIiISOxiTTzMbISZLTGzpWZ2dSPb9zOzGWa20MxmmVlpvW3VZvZi9JgaZ5wiIiIiIhKvVnGd2MzygZuBE4FyYI6ZTXX3V+rtdh1wl7vfaWYnAL8Gzo+2Vbr74LjiExERERGR9ImzxWMosNTd33T3zcA9wOkN9hkAPB69ntnIdhERERERaQHiTDx6AMvrvS+Pyup7CTgren0m0MHMOkfvC81srpk9Z2ZnNHYBMxsd7TN31apVqYxdRERERERSKOnB5d8HjjOzBcBxQAVQHW3bz93LgHOBG83sgIYHu/sEdy9z97KuXbumLWgREREREdk1sY3xICQRPeu9L43KtnL3FUQtHmbWHviiu6+JtlVEz2+a2SxgCLAsxnhFRERERCQmcbZ4zAH6mlkfM2sNnA1sMzuVmXUxs9oYxgATo/KOZtamdh9gGFB/UHpqLJwMNwyEa0rC88LJKb+EiIiIiIjEmHi4+xbgMuBh4FVgsrsvNrNxZnZatNvxwBIzex3oBvwyKu8PzDWzlwiDzsc3mA1rzy2cDA9eDmuXAx6eH7xcyYeIiIiISAzi7GqFu08HpjcoG1vv9RRgSiPHPQMcHGdszBgHVZXbllVVhvJBo2K9tIiINM3MegD7Ua+OcvfZyUUkIiKpEGvikdHWlu9auYiIxM7MfgN8mdC9tnayEQeUeIiIZLncTTyKS6NuVg05PPO/cMS3IS/pSb9ERHLOGUA/d9+UdCAiIpJaufvLevhYKCjatqxVEew7GGaNh3UrkolLRCS3vQkUJB2EiIikXu62eNSO45gxLnSvKi4NycjBX4LVb4b37lAxH0oPTTZWEZHcsQF40cxmAFtbPdz98uRCEhGRVMjdxANC8tHYQPLO0VqFi+6Fey+BoaPhxHHbt5CIiEiqTaXB1OsiItIy5HbisSP9Tw1jPZ67Gd5+Cr74Z+g2IOmoRERaLHe/M1r76cCoaIm7VyUZk4iIpEbujvHYGa3awIhfwVfuhU9WwYTjYcHfko5KRKTFMrPjgTeAm4FbgNfN7NhEgxIRkZRQi8fO6Ps5+OYz8M9vQ7uuSUcjItKS/Q44yd2XAJjZgcAkQIPtRESynBKPndV+bzh3MpiF989PgC59Q0tIwwHqWoBQRGR3FdQmHQDu/rqZaZYrEZEWQInHrqhNOrZshnl3wMrFkNcKaraE8rXL4cFo4hUlHyIiu2Oumf0JuDt6/xVgboLxiIhIimiMx+5o1Rq+9hi0bleXdNSqqgwtICIisju+SVi1/PLo8UpUJiIiWU4tHrurdVvYvKHxbWvL0xuLiEgLEa1Yfn30EBGRFkQtHnuiuLTx8lat4b5L4a3ZUFOT3phERLKQmU2Onl82s4UNH0nHJyIie04tHnti+NgwpqOqsq6soAh6HAZLpsPCe6BkPxh8Lgz+CpT0TC5WEZHM9p3o+QuJRiEiIrFR4rEnageQNzar1eYN8No0WHA3zPo1tO0MQ79el6RoFXQRka3c/b3o5QdApbvXRFPpfhr4V3KRiYhIqijx2FODRjU+g1XrtnXb1rwLhSWh/KVJ8Og1MPAsGHI+9DgEXv6HpuQVEQlmA8eYWUfgEWAO8GXC7FYiIpLFNMYjHUp6QeFe4fW+n4F+I+Cle+BPJ8D1/eGBb4WpePG6KXkXTk40ZBGRhJi7bwDOAm5x9y8BBzV7gNlEM1tpZoua2G5mdpOZLY3GjBxSb9uFZvZG9LgwpZ9ERES2sVstHmbW3t3XpzqYnNDjUDhrAoy8FhbfD9OvgpqqbfepnZJXrR4iknvMzI4ktHBcEpXl7+CYO4A/AHc1sf0UoG/0OBy4FTjczDoBPwXKAAfmmdlUd/9ojz5BIx5YUMG1Dy9hxZpKupcUcdXJ/ThjSI+sO0cmxJAKiiFzYsiUOBRDemLY3a5WrwC9UhZFLioshkMvggevaHy7puQVkdx0BTAGuN/dF5vZ/sDM5g5w99lm1ruZXU4H7nJ3B54zsxIz2xc4HnjU3VcDmNmjwAhg0h5/inoeWFDBmPteprKqGoCKNZWMue9lgJ2u0DPhHJkQQyoohsyJIVPiUAzpi8HC/8ONbDD7blPHAD9y904piSBFysrKfO7cLFzc9oaBUTerBvLy4b/+Av1Pq1sxXURkN5nZPHcvSzqOuESJxzR3H9jItmnAeHd/Kno/A/ghIfEodPdfROU/IQxsv665a+1qfTNs/ONUrKncrrx1fh5DepXs1DkWvLuGzdXbT8+eznNkQgypoBgyJ4ZMiUMxNB9Dj5Iinr76hJ0+T3P1TXNjPH4FdAQ6NHi038FxsiuGj91+hqv8NtCuG0y+AO74AmzZnExsIiJpYmY3Rs8PmtnUho8MiG+0mc01s7mrVq3apWNXNJJ0AI1W8E1pat90niMTYkgFxZA5MWRKHIqh+Ws19X/Y7miuq9V84AF3n9dwg5l9LWUR5LqmpuQ96CxY8Ff44I2wICHAxo/rBqmLiLQsf42em21t2E0VQP2FlEqjsgpCq0f98lmNncDdJwATILR47MrFu5cUNdri0aOkiL9feuROnaOpVpN0niMTYkgFxZA5MWRKHIqh+Ri6l6RuCYjmWi4qgHfM7DuNbGuxzfWJGDQKrlwE16wJz4NGQX4rKLsYRvwq7PPeS2EGrFnjYfMnycYrIpJi9W5yzQWedPcn3P0J4CnClLp7YipwQTS71RHA2mjdkIeBk8ysYzR970lRWUpddXI/igq2HR9fVJDPVSf3y6pzZEIMqaAYMieGTIlDMaQvhuZaPAYArYGvmtldhLEdtaoaP0RiU9QJ+p4YFiOcd2e01seXIU+93kSkRZkBfA6onTmxiLCex1FNHWBmkwgtF13MrJwwU1UBgLvfBkwHRgJLgQ3AxdG21Wb2c+oSm3G1A81TqXZQ5p7MFJMJ58iEGFJBMWRODJkSh2JIXwzNDS6/HPgmsD+h9aN+4uHuvn/KokiBrB1cvqvefR4eHgMV82C/YXDhNFg0RQsQikizsmVwuZm96O6Dd1SWpJypb0REdkNz9U2TLR7ufhNwk5nd6u7fjC062TW9DodLHgvJRuVH4fnBy8PaH1C3ACHsWvKxcLKSFxHJBJ+Y2SHuPh/AzA4FUjeyUUREErPDdTyUdGSgvLy6pOCGgXVJR62qSvjXD6HfKdCmA1SugZotUFgSxo40tHByapIXEZE9dwXwDzNbQWhp3wf4crIhiUisdPMzZ+zuAoKSKZpaaLByNWxaFxKP5/8Is6JB6m32gqKSMGbkomlh+7/HNJ68aPV0EUkzd59jZp8GakczLnF3jSsUaal08zOnKPHIdsWljS9A2GFfaN8tvD7wJCjqGLpmbX2shoK2YfuGDxo/t1ZPF5E0M7O2wHeB/dz962bW18z6ufu0pGMTkRTbuBYe/alufuYQJR7ZbvjYbe8UQFiQ8MRxYfVzgO5DwqMpxT0bT16KS8PzK1OhtAz26p66uDNVJjT3ZkIMmRSH5Jq/APOA2onrK4B/AEo8RLJd9ZYwOc6bM2HZ41A+F7y68X1187NF0lys2W7QKDj1ppA8YOH51Jt27QdiY6unFxSF8so1MOWrcP0AuPNUmH9XKGuJapt71y4HvK65d+Hk3Iohk+KQXHSAu/+WaNp2d9/AtrMqikg2qfyo7vWtR8LEk8KaZDVb4Ogrof3ejR+Xlw9L/gVNzL4q2anJ6XSzjaY33EPN3d3+4A14eQq8PBlWvwn5beCsP8JBZyYbcyptWA23HgXr3mt8e6tC+Oz/wLDvwJp34ZYj2fpbyCy8PvFnYdHHla/BX06JygnbzOCU38DAL0LFfLjn3G23YXDqjTDtysZbn/JawUXTw6xmbz4R/qzy8sHyo+e8cP69+8Obs+D5CWESgq3b8+FzPw1/tm8+AYvv3/74Y74HbTvB20/DpLNh08fbx1HcMyxyKVkni6bTfQYYDjzt7oeY2QHAJHcfmnBoW6m+EWlG5Rp4+8nQorFsZkgwrng51HXz/wpt2kOf40J9A9uP8QDIbx0mxGnfDS6drTXLssxuTacrOWbQqKZbSbr0hc+OgeOvhhXzYeE/YN9oSv0l/4bXpsHBX4LeR9d178p0G1bDO8/A20+Fx/uLgGaS8KGj67qrtW4Ph1wYbfDoboxDlwNDUeFeMPCsaLPX7VPcM9peHBaD3LotOlW7Lk03LddsgdbRmJz8gnCNmmrwmuh5c91doU3rYc07UXl13XPVxrD9o7fDn9nW7TXh+YhvAp3g3WcaTzogxDfvTnj3Weh8AHQ6oO65Tfumvz+RnfdT4N9ATzP7GzAMuCjRiESkadVV4eaYGTz5O3j8F6Fuat0eeh8DB5wQ6pv8VnDI+dsfX/vbo+HNz4POhHX/CUlH5UfwyE/g2Kug437p/XySUmrxkD3z/B/Dfxab10OH7uEH96BRsM+genf8M8CG1bD6LSg9NLz/30Phw6XQqii0IvQ+Gl64Hda/v/2x6bzLf8PAJsbbpLmlobk4hpwP8+6AdSvqylu3hzHldXe0NnwAnT8VEpJOfbbvyidplw0tHmaWB/wXYfXyIwjNis+5exMzYCRD9Y3kNPfQ+2HZ46GF/a3ZcPF02Ofg0KL+9pMh2Sg9LNwoS4U3HoO/nxdukg0dDcd+P0yaIxlJLR4Sn8MvDT9EX/9XaAl5/jZYMh3+e37YXvlRMv85VH5Ur0XjSfjPohDHVcvC3ZOTfhlaHnocAq3ahGNK9mt8oP7wsemLu6nJAtIZw47iGDQKjv8hbP4kVD4fLgszk9Qmmq9OhTceqXcygz7HwIUPhreL7w9d1zp/KnznrVo3HUcmDHBXDGnj7jVm9gN3nww8lHQ8IhJxD//Hv78YJp0TWtUBinuFlon8qB7d/7jwSLW+n4PL58PMX8KzN8OCu0PyceRlmXWTU3ZILR6SWhtWh/+Qug+BLZvgugNDF6RBo8J/Tu26xHPdyjWh+88Bw8MP2Yd/BM/+IfzA7Tk0NPf2Php6HtF8X9FM+IGXCTHsaRwb19YlJR8ug9bt4KjLwrbrD4KPoy5llg8lPcPYl9rk6u2nwgxq774AD1MFb08AACAASURBVF2xffKzq5Mn7InG+h4XFMHnrw8x18orCH+vaqpDt7iGdnZ79ZbtZ3hZdC889N09/h6yocUDwMzGAx8Afwc+qS1399WJBdWA6htpMZr6f766Ksw+tezx8Djw5NDNadN6uP9S2P/40KrRaf/0//B/fzE8OjaMAzlnUnqvLTulufpGiYfEZ9N6mHN7aAlZuTj8yDzgBDh+TF2Xpz05d21rxttPwnsLAYevPgy9jggD4tevDNMA17ZoSGbYsDokI6uXhe5uHy6DfT8DR18Rfnj/slvjP85rtSoKd9S2jm+pDq1uB/8XfLwCJl+w/fiVY74Xtq9aAn/7r7ry2v1GXhsSiXefh7tOqyv3mp37TOffH/5uL74f/nHR9tsveQx6Hha6oU29bPvt33ouTAzw3G3w7x/u3DV3sftdFiUeb9HIgCt33z+BcBql+kZahKZurHQ7GFa9Fsb6WR50PwQOvajx8RlJqqoM8X64DO7/Rkia+hyTdFSCulpJUtq0D1PlHX1luEOxcHKYHav2ju7K10LryAEnhH6gzd1h37gW3nkWOvaGvT8N770Ek74cmnd7Dg3JTO+j6waAd+kbHpJ52nYKj56HNb79wgdDRdLYD3SALZUhwbC8upm5ahMVyw/jTRrO2FVYHLa3bge9jqorr92vuFfY3mGf0H+4tvzJ65r+HPW7v3WKfhPvPaDxbnHFPcJz98GNb2/XNTz3HLr99hnjGr9+y53jfgDwLeBoQgLyJHBbohGJtDQ11fDIjxtfuO/9xTDoS6Fu7nNs5o6lqB07+PGK8LjzC3DgCPjcz8LvBMlIavGQ9KqpCc2yZvCvq+H5W6Ft53CH5d1noXpT3b75rUNz7ierQqLhNWE62xPHhW5c5XOgRxkUFCb1aSROmTDQvgXFkEUtHpOBj4G/RUXnAsXunjGDWlTfSNbZtA7adAivn/wdPHVj07MXYnBNlq3XVVUZxpg+eX2Y7KbsqzDyOo3/SEhz9Y0mRpb0ysur+4/gxHFwzj1hPu+3Zm2bdABUbw6DlAvawbE/gAunhZYNCN2neh+tpKMla25hS8WQ/gkH0megu3/N3WdGj68DA5MOSiRruIdZHF/6O0z7Ltx6NIzvVddK2rF36Hpa1Knx44tL0xZqyhQUhd4Vl78IQy8N72t/a9ROJS8ZQV2tJDmtWkO/U8Jj8f00vo6GwcWa3CYnNTW3ezoH2iuGJMw3syPc/TkAMzscUPOCSFO2bAq9Akr2gw7dQn065eKwrXWHMNbx2B+EtTYgjGcb+EXodWRmzKKYSu06wynj696/9SRM+WpYi2zIBWEtEUlUrH8CZjYC+D2QD/zJ3cc32L4fMBHoCqwGznP38mjbhcCPo11/4e53xhmrJKy4tInuJFl450VSp7mFLRVDS3Uo8IyZvRu97wUsMbOXAXf3QcmFJpIBqiph6QxY/nx4rFgQegiMvA6Gfh32Owo+/zvoeXgYd9bUwr65cFOjcK8wBm/alWHyjhN/FsaBqAtWYmIb42Fm+cDrwIlAOTAHOMfdX6m3zz+Aae5+p5mdAFzs7uebWSfCHa4ywm3wecCh7v5RU9dTn9ss19TsGumcOlWkBcuiMR7NLkvs7u+kK5amqL6RlNiZKctrasIMU8ufg/b7wKdHhunjf9M7TMqy7+AwKUXPw2G/YeGOv2zLHV57CB77aZhJsf+p8OW7k46qRUtqVquhwFJ3fzMK4h7gdOCVevsMAL4bvZ4JPBC9Phl4tHbedjN7FBgBaMLmlioX7ryIyA5lQmIhEruGN9vWLg/vIdR7T/8+rAJePhc2rQ3lA84IiUdRCYyeCV37a5zjzjCD/l8Ia5HMv7NuscOaavi4Akp6JRtfjokz8egB1O87Uw4c3mCfl4CzCN2xzgQ6mFnnJo7tEV+okhFyqzuJiIjkqhnjGp/Kdsa4UA++8ShUfgQHfzG0ZvQcCh371O1bO3W87Lz8Ajjsa3XvX5oUumANHR3Welr6mG5+pkHSo2y+D/zBzC4CZgMVQHWzR9RjZqOB0QC9eiljFRERkSzQ1Do8teXnP6CB0HE74ISQWDx7M8z5c1gPqqYqbGvYAiUpE+d0uhVAz3rvS6Oyrdx9hbuf5e5DgB9FZWt25tho3wnuXubuZV27dk11/CIiIiKp19TEKbXlSjrit1d3OP1m+ObTgNclHbVqW6AkpeJMPOYAfc2sj5m1Bs4Gptbfwcy6mFltDGMIM1wBPAycZGYdzawjcFJUJiIiIpLdho+FvIJty7J9Ktts1e2gMCVxY9Yuhzl/gg+WhkHqssdiSzzcfQtwGSFheBWY7O6LzWycmZ0W7XY8YZrE14FuwC+jY1cDPyckL3OAcbUDzUVERESy2qBRcMYt0GEfwKC4p2ZxTFJTLVCWDw99D/5wKNxwELw1O5QrCdltsbbluft0YHqDsrH1Xk8BpjRx7ETqWkBEREREWoaqSk2okkmGj216Sv8eh8JbT4RZxmoTlBf/Bk/fBPsfB/sfH6YyLipJIvKso06EIiIiIumyZjncNiyML+h/atLRCOx4Sv/OB0DZV+v2b7c3lPSEBXfDCxPA8qD7IXDRtJCwuGuRwiYo8RARERFJl6dvhM0bwuJ/kjl2pQXqwJPCY8tmKJ8TWkRWvxWSDoB7L4FPPqhrEdl3cNMryOcYJR4iIiIi6fDxCph/Fwz5SrhjLtmtVWvoPSw86uv8KVi1JLSgzBgHhcVw6MVw4s+SiTODKPEQERERSYenbgSvgaO/m3QkEqfP/k94rF8VWkPeegLa7x22VW2EW4+E0qGhRaTPcVAcrZG9cHLyixjGHIMSDxEREZG4Va4JrR2fORs67pd0NJIO7bvCwf8VHrU2rg1dr5Y+BgvvCWWdPwX9RsKc2+sGuCexiOHCydsOso8hBiUeIiIiInErKoGvz4A2eyUdiSSpQzf40l+gpgZWvgJvzgotIgvv2XZWLQjv7/8GPHZNWM2+64FhQPvMX21/3kseDS0nz/8Rnv799tu/+TQUdYQnrw9rkzR0+YuhpaOxGGaMU+IhIiIikhVqZznqdlDSkUimyMuDfQaGx1GXwTVNTMfr1XDAZ6FN+/C+uDS8b6hVYXju2Lvx7bULVnY+oPHtlhe6VzWmqfLdoMRDREREJE4zfgZrK+DMP4YfnCINFZeGrk3blfcMUy/X2v/48GjKgSeHR1MGnB4euxRDEwss7gb97RcRERGJyycfhO4voKRDmjZ8bN10vLUKikJ5C4pB/wJERERE4vLszaGf/LHfTzoSyWSDRoWV0ot7AhaeT70pvbNapSEGdbUSERERicOG1WFl64POhK79ko5GMt2uLGKYpTGoxUNEREQkDs/fBpvXw3E/SDoSkYygFg8RERGROJR9FUr2g737Jx2JSEZQi4eIiIhIHDrsA0O+knQUIhlDiYeIiIhIKm1cC3/7EqxYkHQkIhlFiYeIiIhIKr0wAd54BLCkIxHJKEo8RERE4rZwMtwwMKxOfMPA8F5apk3rwhS6B46A7oOTjkYkoyjxEBGRrGdmI8xsiZktNbOrG9m+n5nNMLOFZjbLzErrbfutmS02s1fN7CYzS+1t6oWT4cHLoxWBPTw/ePmuJx9KXrLDC7dD5UdwrGayEmlIs1qJiEhWM7N84GbgRKAcmGNmU939lXq7XQfc5e53mtkJwK+B883sKGAYMCja7yngOGBWygKcMS4sIFdfVSX889vw8hTo0A1O+99Q/uassNJ1UQkUdYKijtC2E7z+cEhWas9Tm7xA8vP+S51N6+HZP8CnPgelhyYdjUjGUeIhIiLZbiiw1N3fBDCze4DTgfqJxwDgu9HrmcAD0WsHCoHWhA75BcD7KY1ubXnj5dWbYd178MnKurLn/whLpm+7X3GvEGZjycuMcelNPBZODtdcWw7FpTB8rBKf+vLy4ZjvQc8jko5EJCMp8RARkWzXA1he7305cHiDfV4CzgJ+D5wJdDCzzu7+rJnNBN4jJB5/cPdXG17AzEYDowF69eq1a9EVl0bdrBqW94RvPLlt2ek3hxaPytWhu86G1eHH7P3faPzcTSU1cajtMqZWl6YVFMGR3046CpGMpTEeIiKSC74PHGdmCwhdqSqAajP7FNAfKCUkMCeY2TEND3b3Ce5e5u5lXbt23bUrDx8bfpDWV1AUyhtq2wm6Hgi9joB+p4Q1ID5zdkheGtNUeRya6jI2Y1z6YshkL/0dFvwN3JOORCRjKfEQEZFsVwH0rPe+NCrbyt1XuPtZ7j4E+FFUtobQ+vGcu6939/XAv4AjUxrdoFFw6k2hhQMLz6fetGutBI0lLwBdPp2yMHeoqdaVdLa6ZKqqSnj0J/DSJEjx3AQiLYm6WomISLabA/Q1sz6EhONs4Nz6O5hZF2C1u9cAY4CJ0aZ3ga+b2a8JXa2OA25MeYSDRu1Zd6TaY+uPr9jnYDjsa6mJb2e06wKfrNq+PJ2tLplq/l9h/fvwxT8nHYlIRlPiISIiWc3dt5jZZcDDQD4w0d0Xm9k4YK67TwWOB35tZg7MBmo74k8BTgBeJgw0/7e7P5juz7BTmktels+B0rL47ra/dA988iEhN2vQlaj30fFcM1ts2QRP3QC9jtJ3IbIDSjxERCTruft0YHqDsrH1Xk8hJBkNj6sGLo09wDgtfwH+fCIceRmc9IvUJh/uMOvX8MRvoM+xcNBZ8OTvolaXHlDUOXQv6jYQjrosddfNJgvuhnUr4Ixb1M1KZAeUeIiIiGSz0sNg6KVh/QgzOPHnqfsBXLUBXn0QBp8HX7gBWrWGsovrtldXwb1fg0d+BHmt4IgmZt9qyYp7wpDzYP/jk45EJOMp8RAREclmZnDKb8Br4Jn/BcuHz12zZ8nHhtVhMHvrdnDxv6CwuPHz5ReEcQ0d9oEDTtj962WzA08KDxHZIc1qJSIiku3MYOS1UPZVePpGePup3T/Xh8vgT5+DqdEaHUUlzScx+a1C4tP1wNA167WHcmNK2eoqePZm2Lg26UhEsoYSDxERkZbADEb+Dr4yBfpstxTJznnn2ZB0VH4Eh12y68cvmQ73nAvTr4Kamt2LIVss/Ds8/D/hOxORnaLEQ0REpKXIy4O+J4bXKxbAU7swM/DLU+Cu08Iihl97LCxiuKv6jYSj/hvm3B5WNa+p3vVzZIPqLTD7Otj3M3DgyUlHI5I1NMZDRESkJXrpHnj+NqjeDMf9oPl9N66Ff/0gDFT/8t0h+dgdtYPbWxXB7N+GqWbPuDV0x2pJFk2Bj96Cs/9PM1mJ7IIW9j+BiIiIAHDyr2DjxzDzl2B5cOz3t9+nuirMRlVYDBc9BJ32h1Zt9uy6ZnDCj8J5Zv0aho6Gnoft2TkzSU01zL4Wuh0cWnhEZKcp8RAREWmJ8vLh9D+E2a4e/3lIPo75bt32yo/g7+dD72Pg+B/C3v1Te/1jvw8HnQmdDwjv3VtG60DlR1CyHxx6Ycv4PCJppMRDRESkpcrLDwvbeXVYaPCle+DxX4QFAPPyQzIw5Pz4rl+bdCx+AF78P/jSHdC6bXzXS4d2XeD8+3Jj5i6RFNPgchERkZYsLx/OuA0GnAbTroC1ywGHmi2hm1U67tpvXg9vPAL/Nwrm3wU3DIRrSsLzwsnxXz9VKubBR++E12rtENllavEQERFp6fJbwcxfQVXltuXVm2DGOBg0Kt7rDzkP8tvAfV+Hd54O3b8gJEEPRuuFxB3DnqqpgX9eFrqsfeMpJR4iu0EtHiIiIrlgbfmulafaoC+F2bK8wfoeVZUh+cl0r02Dla/AsCuUdIjsJiUeIiIiuaC4dNfK47BhdePl6Up+dpc7PPFb6PwpGHhW0tGIZC0lHiIiIrlg+FgoKNq2rKAolKdLk8lPj/TFsDuW/AvefxmO+V4YMyMiu0WJh4iISC4YNApOvQmKewIWnk+9Kb1jKxpLfgDa7AXrV6Yvjl31wRLo3BcO/lLSkYhkNQ0uFxERyRWDRiU7iLv22jPGhe5VxaXQ51hYdC/cOgzO+iMccEJy8TXl6CvhiG9BfkHSkYhktVhbPMxshJktMbOlZnZ1I9t7mdlMM1tgZgvNbGRU3tvMKs3sxehxW5xxioiISJoMGgVXLoJr1oTnM26Brz8ORR3hr2fBsplJR1jHHf6zKLze0xXdRSS+xMPM8oGbgVOAAcA5ZjagwW4/Bia7+xDgbOCWetuWufvg6PGNuOIUERGRhHU7CEbPhBN/FlpAAGqqk40JYNnjcNswWPLvpCMRaRHibPEYCix19zfdfTNwD3B6g30c2Ct6XQysiDEeERERyVSt28Gw74TB2+tXwi1HwCv/TC4ed3jiN7BXKRzw2eTiEGlB4kw8egDL670vj8rquwY4z8zKgenAf9fb1ifqgvWEmR0TY5wiIiKSSbZshNbtYfIFMO272y98mA5vzYblz8PRV6iblUiKJD2r1TnAHe5eCowE/mpmecB7QK+oC9Z3gf8zs70aHmxmo81srpnNXbVqVVoDFxERkZiU9IKvPgxHXQ5z/wy3D4dVS9IbwxO/hQ7d4ZAL0ntdkRYszsSjAuhZ731pVFbfJcBkAHd/FigEurj7Jnf/MCqfBywDDmx4AXef4O5l7l7WtWvXGD6CiIiIJKJVazjp5/CVe2H9+6HbU7qsrYD/vKzWDpEUi3M63TlAXzPrQ0g4zgbObbDPu8Bw4A4z609IPFaZWVdgtbtXm9n+QF/gzRhjFRERkUzU93Pwzachv3V4//GK0A2rcLuOEKlT3AOuWAitCuO7hkgOii3xcPctZnYZ8DCQD0x098VmNg6Y6+5Tge8Bt5vZlYSB5he5u5vZscA4M6sCaoBvuPvquGIVERGRDNZhn/DsDv+4KAw+/6+J0OOQ1F9rw2ooLIGiktSfWyTHxbqAoLtPJwwar182tt7rV4BhjRx3L3BvnLGJiIhIljGDE8fBlEvgzyeF6XeP+FYoT5V7LwGvgQsSnFFLpIVKenC5iIiIyM7rdQR840k48GR4+H/g/74cWilSYfmcsHZHJq6eLtICKPEQERGR7NK2E3z5bhh5HaxbkboB4E/8Boo6QdklqTmfiGxDiYeIiIhkHzMY+nUY/URYfHDzJ/DsLVC9ZffOVzEPlj4KR10GbdqnNlYRAZR4iIiISDbLyw/Pi++Hh8fAnafC2vJdP8+8O8Kg8sO+ntLwRKSOEg8RERHJfkPOgzMnwH8Wwm1Hw2vTd3xMfZ+/Hi6aFu80vSI5TomHiIiItAyf+TJcOjusfH7POfDcbTt3XHUV5BfAPgfHG59IjlPiISIiIi1H5wPgkkdh2HfCzFc78p9FcOPBsPyF+GMTyXFKPERERKRladUmrPfRqU9YdPC+0fDipMb3nX0tbFoPXfqmN0aRHKTEQ0RERFquzethzXJ44Btw36Uhyai18lV45Z9w+KVQ1DG5GEVyRKwrl4uIiIgkqk0HuPDB0LIx+7dQPgcGnxtmsVq7HDAo7pF0lCI5QS0eIiIi0rLlt4LPjoELpsInH8Djv4iSDgAPK6AvnJxoiCK5QImHiIiI5IY+x0CbdoBvW15VCTPGJRKSSC5R4iEiIiK54+P3Gi/fnUUHRWSXKPEQERGR3FFcumvlIpIySjxEREQkdwwfCwVF25YVFIVyEYmVEg8RERHJHYNGwak3QXFPwoxWPcP7QaOSjkykxdN0uiIikvXMbATweyAf+JO7j2+wfT9gItAVWA2c5+7l0bZewJ+AnoRRxyPd/e30RS9pN2iUEg2RBKjFQ0REspqZ5QM3A6cAA4BzzGxAg92uA+5y90HAOODX9bbdBVzr7v2BocDK+KMWEck9SjxERCTbDQWWuvub7r4ZuAc4vcE+A4DHo9cza7dHCUord38UwN3Xu/uG9IQtIpJblHiIiEi26wEsr/e+PCqr7yXgrOj1mUAHM+sMHAisMbP7zGyBmV0btaCIiEiKKfEQEZFc8H3gODNbABwHVADVhLGOx0TbDwP2By5qeLCZjTazuWY2d9WqVWkLWkSkJVHiISIi2a6CMDC8VmlUtpW7r3D3s9x9CPCjqGwNoXXkxaib1hbgAeCQhhdw9wnuXubuZV27do3rc4iItGhKPEREJNvNAfqaWR8zaw2cDUytv4OZdTGz2jpvDGGGq9pjS8ysNps4AXglDTGLiOQcJR4iIpLVopaKy4CHgVeBye6+2MzGmdlp0W7HA0vM7HWgG/DL6NhqQjerGWb2MmDA7Wn+CCIiOUHreIiISNZz9+nA9AZlY+u9ngJMaeLYR4FBsQYoIiJq8RARERERkfgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdgp8RARERERkdjFmniY2QgzW2JmS83s6ka29zKzmWa2wMwWmtnIetvGRMctMbOT44xTRERERETi1SquE5tZPnAzcCJQDswxs6nu/kq93X4MTHb3W81sADAd6B29Phs4COgOPGZmB7p7dVzxioiIiIhIfOJs8RgKLHX3N919M3APcHqDfRzYK3pdDKyIXp8O3OPum9z9LWBpdD4REREREclCsbV4AD2A5fXelwOHN9jnGuARM/tvoB3wuXrHPtfg2B4NL2Bmo4HR0dv1ZrZkz8NOVBfgg6SDyAD6HgJ9D3X0XQR78j3sl8pActm8efM+MLN3ko5jD+nfVKDvIdD3UEffRRBLfRNn4rEzzgHucPffmdmRwF/NbODOHuzuE4AJsUWXZmY2193Lko4jafoeAn0PdfRdBPoeMoO7d006hj2lv0uBvodA30MdfRdBXN9DnIlHBdCz3vvSqKy+S4ARAO7+rJkVEjKsnTlWRERERESyRJxjPOYAfc2sj5m1JgwWn9pgn3eB4QBm1h8oBFZF+51tZm3MrA/QF3ghxlhFRERERCRGsbV4uPsWM7sMeBjIBya6+2IzGwfMdfepwPeA283sSsJA84vc3YHFZjYZeAXYAnw7R2a0ajHdxvaQvodA30MdfReBvgdJFf1dCvQ9BPoe6ui7CGL5Hiz8zhcREREREYmPVi4XEREREZHYKfEQEREREZHYKfFImJn1NLOZZvaKmS02s+8kHVOSzCzfzBaY2bSkY0mSmZWY2RQze83MXo2mm845ZnZl9O9ikZlNima+ywlmNtHMVprZonplnczsUTN7I3rumGSMkl1U32xL9U2g+iZQfZOe+kaJR/K2AN9z9wHAEcC3zWxAwjEl6TvAq0kHkQF+D/zb3T8NfIYc/E7MrAdwOVDm7gMJk1ScnWxUaXUH0XTj9VwNzHD3vsCM6L3IzlJ9sy3VN4HqG9U3d5Cm+kaJR8Lc/T13nx+9Xkf4B7/dKu25wMxKgc8Df0o6liSZWTFwLPBnAHff7O5rko0qMa2AIjNrBbQFViQcT9q4+2xgdYPi04E7o9d3AmekNSjJaqpv6qi+CVTfbEP1zbZiqW+UeGQQM+sNDAGeTzaSxNwI/ACoSTqQhPUhrGfzl6gbwJ/MrF3SQaWbu1cA1xHW+3kPWOvujyQbVeK6uft70ev/AN2SDEayl+ob1TcR1TeovmlCLPWNEo8MYWbtgXuBK9z946TjSTcz+wKw0t3nJR1LBmgFHALc6u5DgE/IwS41UX/S0wkVY3egnZmdl2xUmSNa80jzocsuU32j+qYe1TeovtmRVNY3SjwygJkVECqBv7n7fUnHk5BhwGlm9jZwD3CCmd2dbEiJKQfK3b32TuQUQsWQaz4HvOXuq9y9CrgPOCrhmJL2vpntCxA9r0w4Hskyqm8A1Tf1qb4JVN9sL5b6RolHwszMCH0rX3X365OOJynuPsbdS929N2FA1+PunpN3G9z9P8ByM+sXFQ0HXkkwpKS8CxxhZm2jfyfDycFBjw1MBS6MXl8I/DPBWCTLqL4JVN/UUX2zleqb7cVS3yjxSN4w4HzCHZcXo8fIpIOSxP038DczWwgMBn6VcDxpF92BmwLMB14m/H81IdGg0sjMJgHPAv3MrNzMLgHGAyea2RuEO3Tjk4xRso7qG2mM6hvVN2mrbyx02xIREREREYmPWjxERERERCR2SjxERERERCR2SjxERERERCR2SjxERERERCR2SjxERERERCR2Sjwkp5jZPmZ2j5ktM7N5ZjbdzA40s95mtiima15jZhXR1JWvmNk5O3HMFWbWtt776WZWEkd8IiKSeqpvRLanxENyRrQo0P3ALHc/wN0PBcYA3dJw+RvcfTBwOvDHaPXg5lwBbK0I3H2ku6+JM0AREUkN1TcijVPiIbnks0CVu99WW+DuL7n7k/V3iu5GPWlm86PHUVH5vmY2O7qTtMjMjjGzfDO7I3r/spld2VwA7v4GsAH+n707j7OjKhP//3nS6WwEkpCwJQESHUAWQ4AWRVxAZNhGFsGMqIA6M+h3UBSVEX4yCMw44ozjggqKiuCGIiJERAFZBEcUEpYQAhg2zYJJWBLIRrbn90dVk5tObyFdfXv5vF+v++qqU1WnnluddN3nnnPqMKqs85KImBYRD0XE+WXZ6cBY4LaIuK0seyoixpTLnyjPNzMiPt5lV0eS1FW830itGFjvAKRutBcwvRP7LQQOzcyVEbELcCXQBLwHuDEzPxcRDRTfEE0GxmXmXgAdNU9HxL7A7MxcWBZ9JjOfK+u7JSImZeZFEfEJ4ODMfKbF8fsBHwBeDwTwp4j4XWbe17lLIEnqBt5vpFaYeEgbawS+HhGTgbXArmX5PcBlZbP1tZl5f0Q8AbwqIr4G/Aq4qY06z4iID5R1vaOmfEpEnErxf3EHYA9gRjuxvQn4RWYuA4iIa4A3A94IJKn38X6jfsWuVupPHgL268R+ZwALgL0pvnkaBJCZdwBvAeYBl0fEA70kfgAAIABJREFUyZn5fLnf7cCHge+0UeeXM3NP4HjguxExJCImAp8CDsnMSRQ3kiGv8L1JknoO7zdSK0w81J/cCgwuv/EBICImRcSbW+w3Ang6M9cBJwEN5b47Awsy89sUf/D3LfvBDsjMnwPnAPu2F0BmTgWmAacAWwHLgCURsR1wRM2uLwJbtlLFncCxETEsIrYAjivLJEk9h/cbqRV2tVK/kZkZEccBX4mITwMrgaconuhR62Lg5xFxMvAbij/WAAcBZ0bEamApcDIwDvheRDQn8Wd3IpQLgB8Du1M0WT8CzAH+r2afS4HfRMT8zDy45j3cGxGXA3eXRd+xv60k9Szeb6TWRWbWOwZJkiRJfZxdrSRJkiRVzsRDkiRJUuVMPCRJkiRVzsSjH4qIoRHxu3IW1AkRsaKcHbX5NaiN4yZExMwuOP/tEdHUwT4vz5zayTrfHxFf39zYNlV5Td7TwT6/jojxNevfKK/zrBbX/oQujKvD6xER50XEpzax3qWbF9krExEfj4hhNeu/jYhR9YhFUud5v+k63m+6h/ebapl49E8fBK7JzLXl+uOZObnmtaqewfUyEyhmmG1VRAwFRmfm3OayzDwtMycDR7Lhtb+6PManzW3s4xQz9zb7AfCvdYpFUud5v+k6E/B+0x2831TIxKN/ei9wXVsby29V7oyIe8vXG1vZZ8+IuLv85mRGROxSlr+vpvxbEdHQXiARcUlETIuIhyLi/Bab/y0iHizr+7ty/20i4ucRcU/5OrCD+odHxPfKemZExPFl+Yll2cyI+ELN/ktrlk8oHyVIRFweERdFxB8i4omab4suBN5cvt8zWgnhIIrJntoVEQeV13wqMKvlt30R8amIOK9cfnVE/CYippfHvKaDut8REX+KiPvKb262q9m8d0TcFRGzI+Jfao45s7y+M1r5vbR2jpPLfR+IiB+UZRMi4tay/JaI2Kksv7z227bma15eg9sj4uqIeCQifhSF04GxwG0RcVt52FTgxI7iklR33m+83zTzfiPITF/96EUxK+rfatYnACuA+8vXNygy/SHl9l2AaTX7ziyXvwa8t6bOoRTPCf8l0FiWXwyc3EoMtwNN5fLW5c+GsnxSuf4U8Jly+WTg+nL5x8CbyuWdgIfL5fcDX2/lXF8AvlKzPorij8pfgW0o5rK5FTi23L60Zt8TgMvL5cuBn1Ek63sAj5XlBzXH1sb1vgh4Wxvbaq/nQRTPb5/Yclu5/ingvHL5FmCXcvn1wK2t1P3y9Sjfc/Ojs/8Z+N9y+TzggfJ3N4bi2e5jgb+neK57lO/3euAtLa9Pzbn2BP4MjGnxO/0lcEq5/EHg2ppreULN8UtrrsESYHx53rtqftdPNddfc9xsim/36v7/ypcvXxu/8H7j/cb7ja8WL5vY+p8xwOIWZY9n0RQLQESMAL4eEZOBtcCurdRzF/CZKPqSXpOZsyPiEGA/4J6IgOIPzMIO4pkSxcyuA4EdKP7Izii3XVnz88vl8tuBPcr6AbaKiOHt1P924N3NK5n5fES8Bbg9MxeV7/dHwFuAazuI9dosZped1eJbnPYcSPFHvDPuzswn29uhfK9vBH5Wcw0Gd1DveOCnEbEDxU279hzXZeYKYEX57c7+wJsobgbNE0UNp/hAcEcb9b8N+FlmPgOQmc+V5QcA7yyXfwD8dwdxQnEN5gJExP0UN8Tft7HvQoob17OdqFdS9/N+4/3G+402YOLR/6wAhnSwzxnAAmBvim8CVrbcITN/HBF/Ao4CboiID1F8Y3FFZnZmNlUiYiLFH8nXlX+gL28RW7ayPAB4Q2ZuEFPNH8XNVXvOltfppdpTdlRRRLwKmJOd78O8rGZ5DRt2hWyOZQCwuPbG3QlfA76UmVMj4iCKb56atZxBNCne2+cz81ubcI5N8fJ7i2IG3trBpbXXeC3t/40aQvHvWVLP5P2mfd5vvN/0O47x6Gcy83mgISLauxmMAJ4uv205iaJZegPlH7knMvMiiv67kyiaZE+IiG3LfbaOiJ3bOc9WFH/8lpTf6BzRYvs/1vy8q1y+CfhoTRwd/UG8GTitZv9RwN3AWyNiTBR9gk8EflfusiAidi//QB3XQd0ALwJbtrHtCOA3naijNQuAbSNidEQMBv4BIDNfAJ6MiHeV7yciYu8O6hoBzCuXT2mx7ZiIGBIRoymanu8BbgQ+2PzNXkSMa/6dtuFW4F1lHUTE1mX5H1j/7d97gTvL5acovqkEOBpo7CB+aHGdo7jzb1/WJakH8n7j/abFNu83MvHop26iaN5sy8XAKRHxAPAaNvxmpNkUYGbZPLkX8P3MnAWcA9wUETMo/gjv0NZJMvMBiubVRyj60v5fi11GlfV8jOJbMYDTgaZyANks4MPtvlP4z7KemeX7OTgznwbOAm6j6HM6PTObBz+eRdHH9A/A0x3UDUUz/dooBrm1HOx3OK/wRpCZq4ELKG5aN1Nco2bvBf6pfD8PAcd0UN15FE3l04FnWon/NuCPwH9k5vzMvIni93FXRDwIXE3bNzsy8yHgc8Dvypi+VG76KPCB8nd4EsXvEeDbFDfiByiax1v799XSpcBvagb77Qf8MTPXdOJYSfXj/cb7TW383m/6ueYBQOpHImJf4IzMPKnesfRV5bdG/5eZ7T4/Xq9MRHwVmJqZt9Q7Fklt835TPe831fJ+07Vs8eiHMvNeikfFtfvoQb1ymfmSN4FKzfQmIPV83m+q5/2mct5vupAtHpIkSZIqZ4uHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqXGWJR0RcFhELI2JmG9sjIi6KiMciYkZE7FuzbW1E3F++plYVoyRJkqTuUWWLx+XA4e1sPwLYpXydClxSs21FZk4uX0dXF6IkSZKk7lBZ4pGZdwDPtbPLMcD3s/BHYGRE7FBVPJIkSZLqp55jPMYBc2rW55ZlAEMiYlpE/DEiju3+0CRJkiR1pYH1DqANO2fmvIh4FXBrRDyYmY+33CkiTqXopsUWW2yx32te85rujlOSeoXp06c/k5nb1DsOSVL/Vc/EYx6wY836+LKMzGz++URE3A7sA2yUeGTmpcClAE1NTTlt2rSKQ5ak3iki/lLvGCRJ/Vs9u1pNBU4un271BmBJZj4dEaMiYjBARIwBDgRm1TFOSZIkSZupshaPiLgSOAgYExFzgc8CjQCZ+U3gBuBI4DFgOfCB8tDdgW9FxDqKxOjCzDTxkCRJknqxyhKPzDyxg+0JnNZK+R+A11YVlyRJkqTu11MHl0tSl1q9ejVz585l5cqV9Q6lUkOGDGH8+PE0NjbWOxRJkjZg4iGpX5g7dy5bbrklEyZMICLqHU4lMpNnn32WuXPnMnHixHqHI0nSBuo5uFySus3KlSsZPXp0n006ACKC0aNH9/lWHUlS72TiIanf6MtJR7P+8B4lSb2TiYckdYPFixdz8cUXb/JxRx55JIsXL64gIkmSupeJhyS14tr75nHghbcy8axfceCFt3LtffM2q762Eo81a9a0e9wNN9zAyJEjN+vckiT1BA4ul6QWrr1vHmdf8yArVq8FYN7iFZx9zYMAHLvPuFdU51lnncXjjz/O5MmTaWxsZMiQIYwaNYpHHnmEP//5zxx77LHMmTOHlStX8rGPfYxTTz0VgAkTJjBt2jSWLl3KEUccwZve9Cb+8Ic/MG7cOK677jqGDh3aNW9akqSKmXhI6nfO/+VDzJr/Qpvb7/vrYlatXbdB2YrVa/m3q2dw5d1/bfWYPcZuxWffsWebdV544YXMnDmT+++/n9tvv52jjjqKmTNnvvz0qcsuu4ytt96aFStW8LrXvY7jjz+e0aNHb1DH7NmzufLKK/n2t7/NlClT+PnPf8773ve+zr5tSZLqysRDklpomXR0VP5K7L///hs88vaiiy7iF7/4BQBz5sxh9uzZGyUeEydOZPLkyQDst99+PPXUU10WjyRJVTPxkNTvtNcyAXDghbcyb/GKjcrHjRzKTz90QJfEsMUWW7y8fPvtt/Pb3/6Wu+66i2HDhnHQQQe1+kjcwYMHv7zc0NDAihUbxyhJUk/l4HJJauHMw3ZjaGPDBmVDGxs487DdXnGdW265JS+++GKr25YsWcKoUaMYNmwYjzzyCH/84x9f8XkkSeqpbPGQpBaaB5D/z42PMn/xCsaOHMqZh+32igeWA4wePZoDDzyQvfbai6FDh7Lddtu9vO3www/nm9/8Jrvvvju77bYbb3jDGzb7PUiS1NNEZtY7hi7R1NSU06ZNq3cYknqohx9+mN13373eYXSL1t5rREzPzKY6hSRJkl2tJEmSJFXPxEOSJElS5Uw8JEmSJFXOxEOSJElS5Uw8JEmSJFXOxEOSJElS5Uw8JKkbLF68mIsvvvgVHfuVr3yF5cuXd3FEkiR1LxMPSWrNjKvgy3vBeSOLnzOu2qzqTDwkSf2dM5dLUkszroJfng6rVxTrS+YU6wCTpryiKs866ywef/xxJk+ezKGHHsq2227LVVddxUsvvcRxxx3H+eefz7Jly5gyZQpz585l7dq1/Pu//zsLFixg/vz5HHzwwYwZM4bbbruti96kJEndy8RDUv/0vaM2LtvzWNj/X+C3569POpqtXgG//nSReCx7Fq46ecPtH/hVu6e78MILmTlzJvfffz833XQTV199NXfffTeZydFHH80dd9zBokWLGDt2LL/6VVHXkiVLGDFiBF/60pe47bbbGDNmzOa8Y0mS6squVpLU0gvzWi9f8VyXVH/TTTdx0003sc8++7DvvvvyyCOPMHv2bF772tdy88038+lPf5o777yTESNGdMn5JEnqCWzxkNQ/tddCMWJ80b1qo/Idi59bjO6whaM9mcnZZ5/Nhz70oY223Xvvvdxwww2cc845HHLIIZx77rmv+DySJPUktnhIUkuHnAuNQzcsaxxalL9CW265JS+++CIAhx12GJdddhlLly4FYN68eSxcuJD58+czbNgw3ve+93HmmWdy7733bnSsJEm9lS0ektRS8wDyWy6AJXOLFpBDzn3FA8sBRo8ezYEHHshee+3FEUccwXve8x4OOOAAAIYPH84Pf/hDHnvsMc4880wGDBhAY2Mjl1xyCQCnnnoqhx9+OGPHjnVwuSSp14rMrHcMXaKpqSmnTZtW7zAk9VAPP/wwu+++e73D6BatvdeImJ6ZTXUKSZIku1pJkiRJqp6JhyRJkqTKmXhIkiRJqpyJh6R+o6+MaWtPf3iPkqTeycRDUr8wZMgQnn322T79wTwzefbZZxkyZEi9Q5EkaSM+TldSvzB+/Hjmzp3LokWL6h1KpYYMGcL48ePrHYYkSRsx8ZDULzQ2NjJx4sR6hyFJUr9lVytJkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlatsHo+IuAz4B2BhZu7VyvYAvgocCSwH3p+Z95bbTgHOKXf9z8y8oooYr71vHv9z46PMX7yCsSOHcuZhu3HsPuN6XR1dEUNP0BPehzH0vDjqrSdch54QgyRJm6vKCQQvB74OfL+N7UcAu5Sv1wOXAK+PiK2BzwJNQALTI2JqZj7flcFde988zr7mQVasXgvAvMUrOPuaBwE6fUPvCXV0RQzN9dTzg01XvQ9j6Ftx1FtPuA49IQZJkrpCZYlHZt4RERPa2eUY4PuZmcAfI2JkROwAHATcnJnPAUTEzcDhwJVdGd//3PjoyzfyZitWr+U/rp/F6OGDOlXHf1w/q+51tHX853/9MG/ddRuGDW5gUMMAigam1lX9wWbdumTV2nWsWZesXrOO1WvXsWrtOlavzWJ5zTo+96uHN/tabq6u+H32hRjai+N/bny0X33Y/e8bH6n778PfhSSpr4jic39FlReJx/VtdLW6HrgwM39frt8CfJoi8RiSmf9Zlv87sCIzv9hKHacCpwLstNNO+/3lL3/pdGwTz/oV1b3znmXggGDooAa2GDSQYYPLn4Maitfggdz2yEKWr1q70XHDBjXwD5N2YPXaInFoThpeXl+7jjXNyUO5vnpNi/W1ydp1/eVK9w9v3XUbxo4cwtgRQ9lh5FDGjhzCuJFD2X7EEAYPbKh3eJvkhZWrmb94BU8vXsm8xSuK5SXF8tNLVjDnuRX1DrFNATx54VGd3z9iemY2VReRJEntq7KrVeUy81LgUoCmpqZN+nQ7duRQ5i3e+EPFmOGD+Ob79utUHR/+4XSeWbqqrnW0dfzIoY187O27sHzVWpavWsOyl8qfq9ay/KXi56KlL7H8ueWtJh0Ay1et5Y4/P0PjwKCxYQCDGgbQ2DCAxoZiffjggRusD2oYwMByubFhAIMGrt+2/vigceCAjeo7+5oHeXbZ5l3LzdUVv8++EEN7cQxpHMBzy1Yxc96SNn5fg19OSsaWScnYkUPZYUSRnIwZPpgBA9pufWtpc7oAvrRmLQuWvFSTUKxg3uKVPL2kWJ+/eCVLX1qzwTENA4LttxrC2JFD2HenUTy/bPVG+xTvs/7/JsaOHNot55ckqavUM/GYB+xYsz6+LJtH0epRW357V5/8zMN226B7EcDQxgbOOWoPmiZs3ak6zjlqj7rX0dbx5x29Z6c/oB144a2tJmHjRg7l/856W6fq2FzLV63d7Gu5ubri99kXYmgvjs+/87Uv/7tauXotTy9ZydOLV5QtBCuZXy4/tmgpd8xetFFS29gQbD9iw8RkhxFDGTeyWN9h5BC2GtIItN8F8Oi9x/LMspeYv3j9+efXJhVLVrLoxZc2el+jtxjEDiOHMGH0Frzx1WNqEqMihm22HExDTWLUMobm69AT/k2cedhu3XJ+SZK6Sj27Wh0FfITiqVavBy7KzP3LweXTgX3LXe8F9mse89GWpqamnDZt2ibF1xOeSNUVdXTF8R19yOwO9R7gbgxdG0dm8sKKNS93WyqSkg1bHP72wsqNuuJtOXggO4wcwl+eXc5La9ZtVG/DgKAhglVrN9w2tLHh5USiObHZoewG1tzqMqRx07uC9YTfR1fEYFcrSVK9VZZ4RMSVFC0XY4AFFE+qagTIzG+Wj9P9OsXA8eXABzJzWnnsB4H/r6zqc5n5vY7O90oSD63XEz5cqf9Zuy5Z+OJK5i9e+XJ3qOblm2YtaPO4D7/11TXjTIrkYsTQxnYfotDfmXhIkuqt0haP7mTiIfUtPaELYF9i4iFJqjdnLpfUI5152G4MbdE1yrENkiT1Xr36qVaS+q7mrn52AZQkqW8w8ZDUYx27zzgTDUmS+gi7WkmSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqXKWJR0QcHhGPRsRjEXFWK9t3johbImJGRNweEeNrtq2NiPvL19Qq45QkSZJUrYFVVRwRDcA3gEOBucA9ETE1M2fV7PZF4PuZeUVEvA34PHBSuW1FZk6uKj5JkiRJ3afKFo/9gccy84nMXAX8BDimxT57ALeWy7e1sl2SJElSH1Bl4jEOmFOzPrcsq/UA8M5y+Thgy4gYXa4PiYhpEfHHiDi2tRNExKnlPtMWLVrUlbFLkiRJ6kL1Hlz+KeCtEXEf8FZgHrC23LZzZjYB7wG+EhGvbnlwZl6amU2Z2bTNNtt0W9CSJEmSNk1lYzwokogda9bHl2Uvy8z5lC0eETEcOD4zF5fb5pU/n4iI24F9gMcrjFeSJElSRaps8bgH2CUiJkbEIODdwAZPp4qIMRHRHMPZwGVl+aiIGNy8D3AgUDsoXZIkSVIvUlnikZlrgI8ANwIPA1dl5kMRcUFEHF3udhDwaET8GdgO+FxZvjswLSIeoBh0fmGLp2FJkiRJ6kUiM+sdQ5doamrKadOm1TsMSeqRImJ6OW5OkqS6qPfgckmSJEn9gImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmqnImHJEmSpMqZeEiSJEmq3MD2NkbEJ9rbnplf6tpwJEmSJPVF7SYewJbdEoUkSZKkPq3dxCMzz++uQCRJkiT1XR11tbqove2ZeXrXhiNJkiSpL+qoq9X0bolCkiRJUp/WUVerK7orEEmSJEl9V0ctHgBExDbAp4E9gCHN5Zn5torikiRJktSHdHYejx8BDwMTgfOBp4B7KopJkiRJUh/T2cRjdGZ+F1idmb/LzA8CtnZIkiRJ6pROdbUCVpc/n46Io4D5wNbVhCRJkiSpr+ls4vGfETEC+CTwNWAr4IzKopIkSZLUp3Qq8cjM68vFJcDB1YUjSZIkqS/q1BiPiLgiIkbWrI+KiMuqC0uSJElSX9LZweWTMnNx80pmPg/sU01IkiRJkvqaziYeAyJiVPNKRGxN58eHSJIkSernOps8/C9wV0T8rFx/F/C5akKSJEmS1Nd0dnD59yNiGuvn7nhnZs6qLixJkiRJfUlnu1pBMW/Hssz8OrAoIiZWFJMkSZKkPqazT7X6LPBp4OyyqBH4YVVBSZIkSepbOtvicRxwNLAMIDPnA1tWFZQkSZKkvqWziceqzEwgASJii+pCkiRJktTXdJh4REQA10fEt4CREfEvwG+Bb1cdXOVmXAVf3gvOG1n8nHFVvSOSJEmS+qQOn2qVmRkR7wI+AbwA7Aacm5k3Vx1cpWZcBb88HVavKNaXzCnWASZNqV9ckiRJUh/U2Xk87gUWZ+aZVQbTrW65YH3S0Wz1iqLcxEOSJEnqUp1NPF4PvDci/kI5wBwgMydVElV3WDJ308olSZIkvWKdTTwOqzSKehgxvuhe1dJW47o/FkmSJKmP69RTrTLzL629qg6uUoecC41DNy4fuXP3xyJJkiT1cZsyc3nfMmkKvOMiGLEjEMXP3Y6CedPgmcfqHZ0kSZLUp3S2q1XfNGnKhgPJ162FZ2bDmL+rX0ySJElSH9R/WzxaM6ABtn1NsTzrOlj+XH3jkSRJkvoIE4/WLP4rXP1P8IsPw7p19Y5GkiRJ6vVMPFozcic4/PMw+0b4/ZfqHY0kSZLU61WaeETE4RHxaEQ8FhFntbJ954i4JSJmRMTtETG+ZtspETG7fJ1SZZytet0/w14nwG2fgydu7/bTS5IkSX1JZYlHRDQA3wCOAPYAToyIPVrs9kXg++VEhBcAny+P3Rr4LMXEhfsDn42IUVXF2qoIeMdXYcyuRberlUu69fSSJElSX1Jli8f+wGOZ+URmrgJ+AhzTYp89gFvL5dtqth8G3JyZz2Xm88DNwOEVxtq6wcNhyg/giC/AkBHdfnpJkiSpr6gy8RgH1E4NPrcsq/UA8M5y+Thgy4gY3clju8c2u8JrTyiWl8yrSwiSJElSb1fvweWfAt4aEfcBbwXmAWs7e3BEnBoR0yJi2qJFi6qKsTDnbrhoH5j582rPI0mSJPVBVSYe84Ada9bHl2Uvy8z5mfnOzNwH+ExZtrgzx5b7XpqZTZnZtM0223R1/Bsau0/xuu6jsOjRas8lSZIk9TFVJh73ALtExMSIGAS8G5hau0NEjImI5hjOBi4rl28E/j4iRpWDyv++LKufhkZ41/dg0DD46Unw0tK6hiNJkiT1JpUlHpm5BvgIRcLwMHBVZj4UERdExNHlbgcBj0bEn4HtgM+Vxz4H/AdF8nIPcEFZVl9bjYXjvwvPzoZfng6Z9Y5IkiRJ6hUi+8iH56amppw2bVr3nOz3X4YVz8Mhn4UBDd1zTknaDBExPTOb6h2HJKn/GljvAHqlN52xfjmzmPNDkiRJUptMPDbHnHvg5/8M61bBC0/DiPFwyLkwaUq9I5MkSZJ6FBOPzfHk72DxU+vXl8wpxn6AyYckSZJUo97zePRu0y/fuGz1Crjlgm4PRZIkSerJTDw2x5K5bZf3kUH7kiRJUlcw8dgcI8a3Xf6rT8IPTyhmOl+9snvjkiRJknoYE4/Ncci50Dh0w7LGoUX5iPGw8GG4+oPwxV1h6ukwd3p94pQkSZLqzMHlm6N5APktFxTdq1o+1erAj8NTd8D9V8KDPytmPx+/X9ENa8kcGLlTsd+Mq9quQ5IkSeoDnECwu7y0tBh4Pnwb+Mtd8L3DYec3wehXF4nHmhXr920cCu+4yORDUpdxAkFJUr3Z1aq7DB5eJB0AW78K3nYOvPg03HvFhkkH+GQsSZIk9TkmHvWw5XbwljPho9OBNmY9b+uJWZIkSVIvZOJRTxHtPxlLkiRJ6iNMPOqttSdjNQwqyiVJkqQ+wsSj3iZNKQaSj9gRiCLpIGDsPvWOTJIkSeoyJh49waQpcMZMOG8xnH5fMRD9pyeOt6KAAAAaIUlEQVTBqmX1jkySJEnqEiYePc2I8XD8d2HRI/DLjxVzfkiSJEm9nIlHT/Tqg+Hgz8ATvyseuStJkiT1cs5c3lO9+ZPQ9AHYYky9I5EkSZI2my0ePdWAAUXSsW4t/P4rsOzZekckSZIkvWImHj3ds4/Bbf8F1/xzkYRIkiRJvZCJR0+3zW5w5P/A47fC775Q72gkSZKkV8TEozfY92SY/N4i8Zh9c72jkSRJkjaZiUdvEAFHfhG2ey1cdxqsXlHviCRJkqRN4lOteotBw2DKFbBiMTQOrXc0kiRJ0iYx8ehNRr96/fL8+2DsPvWLRZIkSdoEdrXqjR79DVx6ENx/Zb0jkSRJkjrFxKM3+ru3w4Q3w/VnwN9mdk2dM66CL+8F540sfs64qmvqlSRJkjDx6J0aBsIJl8GQEXDVSbByyebVN+Mq+OXpsGQOkMXPX55u8iFJkqQuY+LRWw3fFt51OTz/F7j2XyGz88euWwuL/gyP/rpYv+WCjZ+UtXpFUS5JkiR1AQeX92Y7HwCHXwgLZ8FXXgtL5sKI8XDIuTBpyob7PnkHPHg1/O1BWPgwrFkBBPx/84rjWrNkTuVvQZIkSf2DLR693dCRMOMnG3aTuvb/wbfeCl/dG557sthvwSx4eCoMHg5NH4RjL4EP3wkDhxTJSqt1b138XLUcrjoZHroWVq/slrclSZKkvsUWj96utW5S69bAgpnwmqOKZYDX/TO8/kPFZIQtHXJuMaajtp7GoXDEF4rl5x6HOXfDrOuKcSV7HQ97vwfGN7VenyRJktSCLR69XVvdpNathSnfhzG7FOsNA9tOEiZNgXdcBCN2BKL4+Y6L1nfX2v61cMZDcNIvYJfDisf4fvftRbctgHXruvQtSZIkqe+xxaO3GzG+9bEYbXWfasukKRuPC6k1oAFe/bbitfIFeOzmIiEBuP5jRZeuye+B3Y8uunNJkiRJNWzx6O0OObfoFlWrcWhRXpUhWxXdrZpbUMbsVrS8XPv/4Iu7wi8+DH/5Q3XnlyRJUq9ji0dv19xKccsF7T/Vqkpv/AgccBrM+RPc/2N46BfFWJCd31h0w3ruCRjzd90XjyRJknqcyE2Z/6EHa2pqymnTptU7DEExSH31Chi2NTz1f3D5kTCuCSafCHu+syiX1K0iYnpmNtU7DklS/2VXK3W9xqHrk4ttdoND/wNWL4dffRL+dzf46UmwdGF9Y5QkSVK3squVqrXFGDjwdHjjR+HpB+CBn8ATt8HQUcX22b+F4dvA9pPgwZ/Vt8uYJEmSKmPioe4RAWMnF6/MYj0TfvNpePYx2HIcLFsI61YX+y+ZU8wtAiYfkiRJfYBdrdT9mp+GFQH/dDMc+UVYvmh90tFs9Qq46TMbT5AoSZKkXscWD9XXsK1h/3+BG85sffvShfBfY2H0LrD9XrDdXrDHMTD61d0bpyRJkjZLpS0eEXF4RDwaEY9FxFmtbN8pIm6LiPsiYkZEHFmWT4iIFRFxf/n6ZpVxqgdoa8LDYaPhLWcWicace+CW84vH80LxxKzvHws3nQMP/BQWzIK1q1uvR5IkSXVVWYtHRDQA3wAOBeYC90TE1MycVbPbOcBVmXlJROwB3ABMKLc9npmTq4pPPcwh5xZjOmq7VTUOhcMv3HCMx4rnYWA5YeLq5cX6ny6FtS8VZQ2D4P/9AcbsAgsfgeXPFK0kQ0d233uRJEnSRqrsarU/8FhmPgEQET8BjgFqE48EtiqXRwDzK4xHPVlnJ0JsfhoWwC6HFq+1a+DZ2fC3B4vXyJ2L7fdeAX+8uFgesSNs/9oiCXnrp6GhjX/6M67yyVqSJEkVqGwCwYg4ATg8M/+5XD8JeH1mfqRmnx2Am4BRwBbA2zNzekRMAB4C/gy8AJyTmXe2dz4nENRGli4qHuG74EH428wiKXnpRfjkw8X26z4Cz/x5fUKydAH8/iuwpkWryzsuMvlQr+cEgpKkeqv34PITgcsz838j4gDgBxGxF/A0sFNmPhsR+wHXRsSemflC7cERcSpwKsBOO+3U3bGrpxu+Dezy9uLVbO2a9ctbT4RnHy9aOV76Tut1rF4Bv/43GDQchm9XtIJsuV21cUuSJPVBVbZ4HACcl5mHletnA2Tm52v2eYiiVWROuf4E8IbMXNiirtuBT2Vmm00atnjoFcuExX+Br+7d8b57HgfvurxY/vbbivEmw7ctkpLh28KOr4cJBxbbX3i6mECxoXHT4rG7lypgi4ckqd6qbPG4B9glIiYC84B3A+9psc9fgUOAyyNid2AIsCgitgGey8y1EfEqYBfgiQpjVX8WAaMmFONAlszZePuWO8C7f1w82nfY1kXZunXF/ksXFt25li2Cl16AN5xWJB6rlsGXXlPsO2z0+sRkn5PgtScULSmzphatMsO3K15Dt4aZV284yN6JFCVJUh9RWeKRmWsi4iPAjUADcFlmPhQRFwDTMnMq8Eng2xFxBsVA8/dnZkbEW4ALImI1sA74cGY+V1WsEtD2k7UOvQDG7bvhvgMGwJQrNixbtRzWNXflCjjqS0VisnRBkZgsXVCTUMyDX5y64fHRAEO22njCxNUr4NdnwZbbF2NRmpMfSZKkXqSyrlbdza5W6hLd1c1p7WpY/NciGVm6oBgIv3QB3Pm/FDl4G/7xh7D7O+CJ2+Ha08puXtuu7+61z0kwaufiMcPLnyvKBw1fP1v8prDLV6EnXIcuiMGuVpKkeqv34HKpZ5k0pXs+VDY0FpMitpyBfcZPW+/uNXx7OP7bsO0exfqQkTDxLUWysmQezL+vaFXZ9Ygi8Xj4ephaPkCucViRgGyxLbzz0mJQ/fz7itfw7Yry5uSlsZwjZcZVdvmCnnEdekIMkiR1AVs8pJ6k5YdM6PwjfdetLX4OaIDnnoQ5fypbUxau7/J1/HeKBOP2L8Dt/7VxHZ96rBh38oUJRatJSyPGwxkPFQPyX0krSm+wZhW8MLe4Zj95Dyx/duN9Bm0J+52yYVnTB4tE8ukHit9jS6//MIzcEebcA7Ou3Xj7gR8rfjdP/R4e/fX68ulXwKoXN95/xI5wxsxOvy1bPCRJ9WaLh9STdHYixdYMaFi/vPXE4tWWN38C9j2pRWLyt/XjR1pLOqBoXQGY+lF45FcbdvMauVMRK8CCWZDrim3DRm8Y26boqm5Oa14qErNBw4r3Nuu69clYc1e3N30cdjsC5t4Dlx/Zfn2rXoTpl29YttsRReLx3JMbb4PioQIjdywmu2xt+34fKK7Xglkbbl+1tPUYlsxtP0ZJknoYWzwkbezLe7Xe5av5W/YHr4a//GF94rJsYfFo4dP+WOz3g+Pg8VuL5RgAW2wD45rgxB8XZdO+B6uX13Tz2q6YH6V2ZvqOWn/Wrlk/aH/ZouLpY9vvBSuXwC8/vj6upQuKsrefXyQXzz0JF00u6hs6av0Txw74COx6WDE25s+/KWK77l+L49u6Dt2ho99FJ9niIUmqNxMPSRvbnC5fUHQ3ev6pmlaFhcWH/EPPL7Zf8qZiRvlaE94M77++WP7pSTD7JlizcuO6R4wvukMtW8QGA/H3/xAc+d9F68bFB5QJxTbrE4uJB8GOrysSlqULimRo4KBqr0NX6KIYTDwkSfVmVytJG9ucLl8AO+xdvNry4Tth5eINE5PBW63fHgNaTzqg6O51wGnlbPLbrp8HZeROxfaBg+H0e9s+d8NAGDGuc+9jc69DV+gJMUiS1AVs8ZDUM3VRFyMVbPGQJNXbgHoHIEmtOuTc9Y/3bdY4dP0AdkmS1KuYeEjqmSZNKcYxjNgRiOJnd46tkCRJXcoxHpJ6ru6a0FGSJFXOFg9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklQ5Ew9JkiRJlTPxkCRJklS5ShOPiDg8Ih6NiMci4qxWtu8UEbdFxH0RMSMijqzZdnZ53KMRcViVcUqSJEmq1sCqKo6IBuAbwKHAXOCeiJiambNqdjsHuCozL4mIPYAbgAnl8ruBPYGxwG8jYtfMXFtVvJIkSZKqU2WLx/7AY5n5RGauAn4CHNNinwS2KpdHAPPL5WOAn2TmS5n5JPBYWZ8kSZKkXqiyFg9gHDCnZn0u8PoW+5wH3BQRHwW2AN5ec+wfWxw7ruUJIuJU4NRydWlEPLr5YdfVGOCZegfRA3gdCl6H9bwWhc25Djt3ZSCSJG2qKhOPzjgRuDwz/zciDgB+EBF7dfbgzLwUuLSy6LpZREzLzKZ6x1FvXoeC12E9r0XB6yBJ6s2qTDzmATvWrI8vy2r9E3A4QGbeFRFDKL7R68yxkiRJknqJKsd43APsEhETI2IQxWDxqS32+StwCEBE7A4MARaV+707IgZHxERgF+DuCmOVJEmSVKHKWjwyc01EfAS4EWgALsvMhyLiAmBaZk4FPgl8OyLOoBho/v7MTOChiLgKmAWsAU7rJ0+06jPdxjaT16HgdVjPa1HwOkiSeq0oPudLkiRJUnWcuVySJElS5Uw8JEmSJFXOxKPOImLHiLgtImZFxEMR8bF6x1RPEdEQEfdFxPX1jqWeImJkRFwdEY9ExMPl46b7nYg4o/x/MTMiriyffNcvRMRlEbEwImbWlG0dETdHxOzy56h6xihJ0qYw8ai/NcAnM3MP4A3AaRGxR51jqqePAQ/XO4ge4KvAbzLzNcDe9MNrEhHjgNOBpszci+IhFe+ub1Td6nLKx43XOAu4JTN3AW4p1yVJ6hVMPOosM5/OzHvL5RcpPmBuNEt7fxAR44GjgO/UO5Z6iogRwFuA7wJk5qrMXFzfqOpmIDA0IgYCw4D5dY6n22TmHcBzLYqPAa4ol68Aju3WoCRJ2gwmHj1IREwA9gH+VN9I6uYrwL8B6+odSJ1NpJjP5ntlt7PvRMQW9Q6qu2XmPOCLFPP9PA0sycyb6htV3W2XmU+Xy38DtqtnMJIkbQoTjx4iIoYDPwc+npkv1Due7hYR/wAszMzp9Y6lBxgI7Atckpn7AMvoh11qyvELx1AkYmOBLSLiffWNquco5zzyeeiSpF7DxKMHiIhGiqTjR5l5Tb3jqZMDgaMj4ingJ8DbIuKH9Q2pbuYCczOzueXraopEpL95O/BkZi7KzNXANcAb6xxTvS2IiB0Ayp8L6xyPJEmdZuJRZxERFH35H87ML9U7nnrJzLMzc3xmTqAYQHxrZvbLb7cz82/AnIjYrSw6BJhVx5Dq5a/AGyJiWPn/5BD64SD7FqYCp5TLpwDX1TEWSZI2iYlH/R0InETxDf/95evIegeluvso8KOImAFMBv6rzvF0u7LF52rgXuBBir9Xl9Y1qG4UEVcCdwG7RcTciPgn4ELg0IiYTdEidGE9Y5QkaVNE0U1YkiRJkqpji4ckSZKkypl4SJIkSaqciYckSZKkypl4SJIkSaqciYckSZKkypl4qF+JiO0j4icR8XhETI+IGyJi14iYEBEzKzrneRExr3xU8qyIOLETx3w8IobVrN8QESOriE+SJKk7mHio3ygnofsFcHtmvjoz9wPOBrbrhtN/OTMnA8cA3ypnq2/Px4GXE4/MPDIzF1cZoCRJUpVMPNSfHAyszsxvNhdk5gOZeWftTmXrx50RcW/5emNZvkNE3FG2XMyMiDdHRENEXF6uPxgRZ7QXQGbOBpYDo8o6L4mIaRHxUEScX5adDowFbouI28qypyJiTLn8ifJ8MyPi4112dSRJkio0sN4BSN1oL2B6J/ZbCByamSsjYhfgSqAJeA9wY2Z+LiIaKFokJgPjMnMvgI66Q0XEvsDszFxYFn0mM58r67slIiZl5kUR8Qng4Mx8psXx+wEfAF4PBPCniPhdZt7XuUsgSZJUHyYe0sYaga9HxGRgLbBrWX4PcFnZTerazLw/Ip4AXhURXwN+BdzURp1nRMQHyrreUVM+JSJOpfi/uAOwBzCjndjeBPwiM5cBRMQ1wJsBEw9JktSj2dVK/clDwH6d2O8MYAGwN0VLxyCAzLwDeAswD7g8Ik7OzOfL/W4HPgx8p406v5yZewLHA9+NiCERMRH4FHBIZk6iSFyGvML3JkmS1KOZeKg/uRUYXLYwABARkyLizS32GwE8nZnrgJOAhnLfnYEFmfltigRj33LcxYDM/DlwDrBvewFk5lRgGnAKsBWwDFgSEdsBR9Ts+iKwZStV3AkcGxHDImIL4LiyTJIkqUezq5X6jczMiDgO+EpEfBpYCTxF8QSpWhcDP4+Ik4HfUCQHAAcBZ0bEamApcDIwDvheRDQn8Wd3IpQLgB8Du1N0kXoEmAP8X80+lwK/iYj5mXlwzXu4NyIuB+4ui77j+A5JktQbRGbWOwZJkiRJfZxdrSRJkiRVzsRDkiRJUuVMPCRJkiRVzsSjH4qIoRHxu3LW7QkRsaKcjbv5NaiN4yZExMwuOP/tEdHUwT4vz9TdyTrfHxFf39zYNlV5Td7TwT6/jojxNevfKK/zrBbX/oQujKvD6xER50XEpzax3qWbF9krExEfj4hhNeu/jYhR9YhFkiS9MiYe/dMHgWsyc225/nhmTq55rapncL3MBIoZzVsVEUOB0Zk5t7ksM0/LzMnAkWx47a8uj/Fpcxv7OMVM8c1+APxrnWKRJEmvgIlH//Re4Lq2Npbf4t8ZEfeWrze2ss+eEXF3+U39jIjYpSx/X035tyKiob1AIuKSiJgWEQ9FxPktNv9bRDxY1vd35f7bRMTPI+Ke8nVgB/UPj4jvlfXMiIjjy/ITy7KZEfGFmv2X1iyfUD66loi4PCIuiog/RMQTNa0TFwJvLt/vGa2EcBDF5ILtioiDyms+FZjVsnUpIj4VEeeVy6+OiN9ExPTymNd0UPc7IuJPEXFf2VKwXc3mvSPiroiYHRH/UnPMmeX1ndHK76W1c5xc7vtARPygLJsQEbeW5bdExE5l+eW1rTvN17y8BrdHxNUR8UhE/CgKpwNjgdsi4rbysKnAiR3FJUmSeg4Tj36m7Eb1qsx8qqb41TXdfb4BLAQOzcx9gX8ELmqlqg8DXy2/uW8C5kbE7uX+B5blaymSnPZ8JjObgEnAWyNiUs22JZn5WuDrwFfKsq9SzAL+OopZwNuaKbzZvzfXU84OfmtEjAW+ALwNmAy8LiKO7aAegB2ANwH/QJFwAJwF3Fm2WHy5lWOOoJgLpDP2BT6Wmbt2sN+lwEczcz+Kmc8v7mD/3wNvyMx9gJ8A/1azbRLFdTgAODcixkbE3wO7APtTXJ/9IuItbVUeEXtSTJ74tszcG/hYuelrwBXldf8Rrf87amkfitaNPYBXUfxbugiYDxzcPKdJOWP84IgY3Yk6JUlSD2CXjv5nDLC4RdnjZaIAQESMAL4eEc3JQ2sfhO8CPlOOXbgmM2dHxCHAfsA9EQEwlCKJac+UKGYSH0jxwX4PYEa57cqan80f6t8O7FHWD7BVRAxvp/63A+9uXsnM58sP0bdn5qLy/f4IeAtwbQexXlvOZj6rRatBew6kSA464+7MfLK9Hcr3+kbgZzXXYHAH9Y4HfhoROwCDgNpzXJeZK4AVZWvC/hTJ1d9TTG4IMJwiEbmjjfrfBvwsM58ByMznyvIDgHeWyz8A/ruDOKG4BnMBIuJ+iq5sv29j34UULSHPdqJeSZJUZyYe/c8KYEgH+5wBLAD2pmgVW9lyh8z8cUT8CTgKuCEiPgQExTfcnZm9m4iYSPGh/HVlQnB5i9iyleUBFN/ebxBTzYfwzVV7zpbX6aXaU3ZUUUS8CpizCWNmltUsr2HDFsnmWAYAi2sTxU74GvClzJwaEQcB59VsazmDaFK8t89n5rc24Ryb4uX3FsWM77UPM6i9xmtp/2/UEIp/z5IkqRewq1U/U3ZRaYiI9pKPEcDT5bf7JwEbjdMoP1Q/UXaDuY6iy84twAkRsW25z9YRsXM759mK4sP2krIF4YgW2/+x5udd5fJNwEdr4ujoA/jNwGk1+48C7qbo1jWmHINyIvC7cpcFEbF7+YH4uA7qBngR2LKNbZvSzaqlBcC2ETE6IgZTdO8iM18AnoyId5XvJyJi7w7qGgHMK5dPabHtmIgYUnZZOgi4B7gR+GBzS1JEjGv+nbbhVuBdzd2eImLrsvwPrG9tei9wZ7n8FEXLGMDRQGMH8UOL6xxFprl9WZckSeoFTDz6p5soutO05WLglIh4AHgNG34T32wKMLPsDrMX8P3MnEXR1/+miPj/27l/nSiiMAzjz7kES25DvQE6Oi7AbGGoldBREv+0JrbSW1EZCqMhhIKwzZosLsYrkMYbMEpei3M2mMmyEOIEWJ5fO7tnz+xMMW++75tj6kP/0kU/kmRMbef5DrwHDjsfedDWWadWYQCeA4/bwPI36qzJPK/aOpN2PstJTqmzGfvAGBglmQ7bbwK71Ifm00vWhtoWdtaGqrvD5StcM3gk+Q28oIakz9T/aOoJsNbO5wRYvWS5LWpr1gj4OWP/+8AQeJnkR5JP1OtxVEr5CuxwcbgiyQnwGjhoe3rTDj0DnrZrOOB89mObGvzG1HasWfdX1zvg4z/D5Y+AYZI/V/iuJEm6BUrS7bTQoiulPAQ2kgxuei+LqlUpDtvgvP6zUspb4EOSvZveiyRJuhorHvdQki/UV5POfdWtri/JL0NHryaGDkmS7hYrHpIkSZJ6Z8VDkiRJUu8MHpIkSZJ6Z/CQJEmS1DuDhyRJkqTeGTwkSZIk9e4vuURWmm4i2DAAAAAASUVORK5CYII=\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_results(rus_results, ratios, [\"tn\", \"fp\", \"fn\", \"tp\",])" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 671 | |
| }, | |
| "id": "MohvOy1KJiqZ", | |
| "outputId": "5cf4d380-86a4-4269-adaa-a6471304025b" | |
| }, | |
| "execution_count": 24, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 4 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "f1, recall重視であればratio=1を、precision重視であればratio=7を選択する。\n", | |
| "\n", | |
| "ratio=1で性能を見てみる。" | |
| ], | |
| "metadata": { | |
| "id": "lJ21u95MXrtV" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from imblearn.pipeline import Pipeline\n", | |
| "from imblearn.under_sampling import RandomUnderSampler\n", | |
| "from sklearn.ensemble import RandomForestClassifier\n", | |
| "\n", | |
| "neg, pos = np.bincount(train_labels)\n", | |
| "total = neg + pos\n", | |
| "print('Examples:\\n Total: {}\\n Positive: {} ({:.2f}% of total)\\n'.format(\n", | |
| " total, pos, 100 * pos / total))\n", | |
| "train_f_count = neg\n", | |
| "train_t_count = pos\n", | |
| "\n", | |
| "under_sampling_rate = 1\n", | |
| "sampler = RandomUnderSampler(\n", | |
| " sampling_strategy = {0 : int(train_t_count * under_sampling_rate), 1 : train_t_count}, \n", | |
| " random_state = 42\n", | |
| ")\n", | |
| "\n", | |
| "classifier = RandomForestClassifier(\n", | |
| " random_state = 42,\n", | |
| " n_jobs = -1\n", | |
| ")\n", | |
| "\n", | |
| "train_res_df, train_res_labels = sampler.fit_resample(train_df, train_labels)\n", | |
| "classifier.fit(train_res_df, train_res_labels)" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "IWLSXiEPW36f", | |
| "outputId": "bfa8b922-1004-4591-9e3a-8965537509ce" | |
| }, | |
| "execution_count": 25, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Examples:\n", | |
| " Total: 182276\n", | |
| " Positive: 330 (0.18% of total)\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "RandomForestClassifier(n_jobs=-1, random_state=42)" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 25 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "train_predictions_undersampled_t1 = classifier.predict_proba(train_df)\n", | |
| "test_predictions_undersampled_t1 = classifier.predict_proba(test_df)\n", | |
| "train_predictions_undersampled_t1_proba_t = train_predictions_undersampled_t1.T[1]\n", | |
| "test_predictions_undersampled_t1_proba_t = test_predictions_undersampled_t1.T[1]\n", | |
| "\n", | |
| "plot_cm(test_labels, test_predictions_undersampled_t1_proba_t)\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 439 | |
| }, | |
| "id": "B1H7y81wYZ81", | |
| "outputId": "47558391-bae7-4f71-93e2-f6746df9e4f3" | |
| }, | |
| "execution_count": 26, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Legitimate Transactions Detected (True Negatives): 55329\n", | |
| "Legitimate Transactions Incorrectly Detected (False Positives): 1535\n", | |
| "Fraudulent Transactions Missed (False Negatives): 8\n", | |
| "Fraudulent Transactions Detected (True Positives): 90\n", | |
| "Total Fraudulent Transactions: 98\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 360x360 with 2 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_roc(\"Train base (NOT Undersampled)\", train_labels, train_predictions_undersampled_proba_t, color=colors[0])\n", | |
| "plot_roc(\"Test base (NOT Undersampled)\", test_labels, test_predictions_undersampled_proba_t, color=colors[0], linestyle='--')\n", | |
| "\n", | |
| "plot_roc(\"Train Undersampled 1:1\", train_labels, train_predictions_undersampled_t1_proba_t, color=colors[1])\n", | |
| "plot_roc(\"Test Undersampled 1:1\", test_labels, test_predictions_undersampled_t1_proba_t, color=colors[1], linestyle='--')\n", | |
| "plt.legend(loc='lower right');\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 606 | |
| }, | |
| "id": "Q-GCs4WXYv8D", | |
| "outputId": "49b2b53c-a697-47cb-e410-8584136755ef" | |
| }, | |
| "execution_count": 27, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_prc(\"Train base (NOT Undersampled)\", train_labels, train_predictions_undersampled_proba_t, color=colors[0])\n", | |
| "plot_prc(\"Test base (NOT Undersampled)\", test_labels, test_predictions_undersampled_proba_t, color=colors[0], linestyle='--')\n", | |
| "\n", | |
| "plot_prc(\"Train Undersampled 1:1\", train_labels, train_predictions_undersampled_t1_proba_t, color=colors[1])\n", | |
| "plot_prc(\"Test Undersampled 1:1\", test_labels, test_predictions_undersampled_t1_proba_t, color=colors[1], linestyle='--')\n", | |
| "plt.legend(loc='lower right');" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 606 | |
| }, | |
| "id": "Cj_gzhiSZHF0", | |
| "outputId": "8d11ba77-6113-43f4-cd60-bcdde9be7a90" | |
| }, | |
| "execution_count": 28, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "思っていたよりFP数が多かったので、ratio=7でも性能を見てみる。" | |
| ], | |
| "metadata": { | |
| "id": "y2heZx5MtQtr" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from imblearn.pipeline import Pipeline\n", | |
| "from imblearn.under_sampling import RandomUnderSampler\n", | |
| "from sklearn.ensemble import RandomForestClassifier\n", | |
| "\n", | |
| "neg, pos = np.bincount(train_labels)\n", | |
| "total = neg + pos\n", | |
| "print('Examples:\\n Total: {}\\n Positive: {} ({:.2f}% of total)\\n'.format(\n", | |
| " total, pos, 100 * pos / total))\n", | |
| "train_f_count = neg\n", | |
| "train_t_count = pos\n", | |
| "\n", | |
| "under_sampling_rate = 7\n", | |
| "sampler = RandomUnderSampler(\n", | |
| " sampling_strategy = {0 : int(train_t_count * under_sampling_rate), 1 : train_t_count}, \n", | |
| " random_state = 42\n", | |
| ")\n", | |
| "\n", | |
| "classifier = RandomForestClassifier(\n", | |
| " random_state = 42,\n", | |
| " n_jobs = -1\n", | |
| ")\n", | |
| "\n", | |
| "train_res_df, train_res_labels = sampler.fit_resample(train_df, train_labels)\n", | |
| "classifier.fit(train_res_df, train_res_labels)" | |
| ], | |
| "metadata": { | |
| "id": "aJPkKD9MZJDO", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "8a3a41a4-168a-4220-8e22-a32f46d81311" | |
| }, | |
| "execution_count": 29, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Examples:\n", | |
| " Total: 182276\n", | |
| " Positive: 330 (0.18% of total)\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "RandomForestClassifier(n_jobs=-1, random_state=42)" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 29 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "train_predictions_undersampled_t2 = classifier.predict_proba(train_df)\n", | |
| "test_predictions_undersampled_t2 = classifier.predict_proba(test_df)\n", | |
| "train_predictions_undersampled_t2_proba_t = train_predictions_undersampled_t2.T[1]\n", | |
| "test_predictions_undersampled_t2_proba_t = test_predictions_undersampled_t2.T[1]\n", | |
| "\n", | |
| "plot_cm(test_labels, test_predictions_undersampled_t2_proba_t)\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 439 | |
| }, | |
| "id": "fvTKgqK5pGVc", | |
| "outputId": "f8855cbc-196e-4332-8027-49af34e5fdb4" | |
| }, | |
| "execution_count": 30, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Legitimate Transactions Detected (True Negatives): 56776\n", | |
| "Legitimate Transactions Incorrectly Detected (False Positives): 88\n", | |
| "Fraudulent Transactions Missed (False Negatives): 13\n", | |
| "Fraudulent Transactions Detected (True Positives): 85\n", | |
| "Total Fraudulent Transactions: 98\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 360x360 with 2 Axes>" | |
| ], | |
| "image/png": 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78cILf6NPn94MHrwJAPsM3YMXX3y5ktW0DlauPs4fA5MlvQy8lcq+AGwKnFSm1+xwH8ydxym/OBeAZQ3L2G/Ynuw2ZAeWLl3KL//zQg783vGstlo3/vOXpy3vs5w24znWX7c/gwZ+NvhNfPAxLr/gnBXKdt3pa/x5ypMccMRounbpymknjqJvn97lf3MGwJSpT3HHHfcwdcpEGhoamDFjJldd/Qdm18/h1lvG0NgYzJ83n2NGn1bpqlZelTa7i6Eo071XkrqQNc0LB4emRsSy9py/9P1Xa+en8DlTt8Hula6CrYKGT+pVzHlLfvW9on5ne/7yxqJer5LKNqoeEY3AE+W6vpl1MjWUcfo+TjMrjSod6CmGA6eZlYYzTjOznGroBngHTjMrjRrKOMt1H6eZ1Zhy3gAvqaukpyTdnbY3lvRXSbMk3SKpeypfPW3PSvs3KrjGz1P5S5L2LSgfnspmtffJRgdOMyuN8j5yeQpQOM/F+cCFEbEpMI9Pn0gcBcxL5Rem45C0JXAosBUwHLg8BeOuwGXACGBL4LB0bJscOM2sNMoUOCVtCHwTuDptC9gb+N90yFjgwLQ+Mm2T9g9Nx48Ebo6If0TEa8AssvvMdwRmRcSrEfEJ2RwbI1dWJwdOMyuNaCxqKZyjIi2jm135f4B/49PHtdcG5kdEQ9qezacP2gwkPa2Y9i9Ixy8vb3ZOa+Vt8uCQmZVGkYNDETEGGNPSPknfAt6LiOmS9iy+cqXlwGlmJRHlGVXfFThA0n5AD6A3cBHQV1K3lFVuSPZIN+nrIGC2pG5AH+CDgvImhee0Vt4qN9XNrDTK0McZET+PiA0jYiOywZ0HI+II4CHg2+mwo4C70vr4tE3a/2BkE3KMBw5No+4bA4PJ5gmeCgxOo/Td02uMX9lbdcZpZqXRsY9c/gy4WdKvgKeAa1L5NcANkmYBc8kCIRExU9KtwPNAA3Bi04RDkk4CJgJdgWsjYubKXrxssyOtKs+OVL08O1J1K3Z2pEUnjCjqd7bX5RM8O5KZ1Sg/OWRmZq1xxmlmJdFZu/3KwYHTzEqjhprqDpxmVhoOnGZm+ZTpBvhOyYHTzErDgdPMLKfamQDegdPMSsNNdTOzvBw4zcxyclPdzCwfN9XNzPJyxmlmlo8zTjOzvJxxmpnlEw6cZmY5OXCameVTSxmnJzI2M8vJGaeZlUYNZZwOnGZWErXUVHfgNLOScOA0M8vJgROQtAhoehSg6XOPI61HRPQuc93MrJpE1X08etFaDZwR0asjK2Jm1c0ZZzOSdgMGR8R1kvoDvSLitfJWzcyqSTQ641xO0pnADsDmwHVAd+BGYNfyVs3MqokzzhUdBGwHPAkQEW9LcjPezFYQ7uNcwScREZICQFLPMtfJzKqQM84V3Srpd0BfSccCRwNXlbdaZlZt3MdZICIukPRPwEJgM+CMiJhU9pqZWVWJ2pnHuN03wD8L1JHdx/ls+apjZtWqljLOlc6OJOkYYApwMPBt4AlJR5e7YmZWXaJRRS3VqD0Z50+B7SLiAwBJawN/Bq4tZ8XMrLq4qb6iD4BFBduLUpmZ2XLVmj0Wo61n1f81rc4C/irpLrI+zpHAMx1QNzOzTqmtjLPpJvdX0tLkrvJVx8yqlW+AByLi7I6siJlVt1q6Ab49o+rrSPq1pHslPdi0dETlzKx6NIaKWlZGUg9JUyQ9LWmmpLNT+caS/ipplqRbJHVP5aun7Vlp/0YF1/p5Kn9J0r4F5cNT2SxJp6+sTu35sLY/AC8CGwNnA68DU9txnpnVkAgVtbTDP4C9I2IbYFtguKQhwPnAhRGxKTAPGJWOHwXMS+UXpuOQtCVwKLAVMBy4XFJXSV2By4ARwJbAYenYVrUncK4dEdcASyPikYg4Gti7Pe/WzGpHue7jjMzitLlaWoIsDv1vKh8LHJjWR6Zt0v6hkpTKb46If6RpMWcBO6ZlVkS8GhGfADenY1vVnsC5NH2dI+mbkrYD1mrHeWZWQyKKW9ojZYYzgPeASWQD1vMjoiEdMhsYmNYHAm9ldYoGYAGwdmF5s3NaK29Ve+7j/JWkPsBpwCVAb+DUdpxnZjWk2Ps4JY0GRhcUjYmIMStcO2IZsK2kvsCdwBbF1rMU2jPJx91pdQGwV3mrY2bVqj0DPS1JQXLMSg/Mjp0v6SFgZ7IZ27qlrHJDoD4dVg8MAmZL6gb0IXtop6m8SeE5rZW3qK0b4C/h0w9ra+kNnNzWhc2stpTrPk5J65CNscyXVAf8E9mAz0Nk82fcDBzFp/eYj0/bf0n7H0xzCo8HbpL0W2ADYDDZPBwCBkvamCxgHgoc3lad2so4pxX1Ls2sJpXxWfUBwNg0+t0FuDUi7pb0PHCzpF8BTwHXpOOvAW6QNAuYSxYIiYiZkm4FngcagBNTFwCSTgImAl2BayNiZlsVUnTSJ/OXvv9q56yYrVTdBrtXugq2Cho+qS8qdZzxxQOK+p3d9o3xVffIUXvn4zQza5MfuTQzy6mTNl7LotMGTjf3zKpLsaPq1cij6mZWEm6qZzyqbmbt5owTiIixre0zM6tlK+3jTDef/oxs1pAeTeUR4Yk+zGy5Ghobave0ci/gaeXMrA3lmo+zM/K0cmZWEmWcj7PTac/tSCtMKwe8jaeVM7NmauiTMzytnJmVRlCd2WMxPK2cmZVEYw2NDrVnVP06WhgwS32dZmYANDrjXMHdBes9gIPI+jnNzJZzU71ARNxeuC1pHPB42WpkZlXJg0NtGwysW+qKmFl1c8ZZQNIiVuzjfIfsSSIzs+WccRaIiF4dUREzq261FDhX+uSQpMntKTOz2haoqKUatTUfZw9gDaC/pH6w/B32ZiUf1m5mtafIj1WvSm011Y8Dfkz2MZrT+TRwLgQuLXO9zKzK+D5OICIuAi6S9KOIuKQD62RmVaiGHhxq1+xIjZL6Nm1I6ifphDLWycysU2tP4Dw2IuY3bUTEPODY8lXJzKpRY5FLNWrPDfBdJSki+/BPSV2B7uWtlplVm0a5j7PQfcAtkn6Xto9LZWZmy9VSH2d7AufPgNHAD9P2JOCqstXIzKpStTa7i7HSPs6IaIyIKyPi2xHxbeB5sgmNzcyWa1RxSzVq1yQfkrYDDgMOAV4D7ihnpcys+vg+TkDSZmTB8jDgfeAWQBHhWeDN7DPcx5l5EXgM+FZEzAKQ5M8aMrMWVWuzuxht9XEeDMwBHpJ0laShUEO5uJnlUkv3cbYaOCPijxFxKLAF8BDZc+vrSrpC0rCOqqCZVYcocqlG7RlVXxIRN0XE/sCGwFN4ImMza6aWRtXb88jlchExLyLGRMTQclXIzKpTLTXVi/nMITOzz6jWIFgMB04zK4mo0mZ3MRw4zawknHGameVUS4Ez1+CQmVlrynU7kqRBkh6S9LykmZJOSeVrSZok6eX0tV8ql6SLJc2S9Iyk7QuudVQ6/mVJRxWUf03Ss+mci6W258hz4DSzzq4BOC0itgSGACdK2hI4HZgcEYOByWkbYAQwOC2jgSsgC7TAmcBOwI7AmU3BNh1zbMF5w9uqkAOnmZVEue7jjIg5EfFkWl8EvED2SbsjgbHpsLHAgWl9JHB9ZJ4A+koaAOwLTIqIuemTLCYBw9O+3hHxRJqw/fqCa7XIfZxmVhId0ccpaSNgO+CvwHoRMSftegdYL60PBN4qOG12KmurfHYL5a1yxmlmJVHsDfCSRkuaVrCMbun6ktYEbgd+HBELC/elTLHDnuB0xmlmJVFs1IqIMcCYto6RtBpZ0PxDRDTNB/yupAERMSc1t99L5fXAoILTN0xl9cCezcofTuUbtnB8q5xxmllJlKuPM41wXwO8EBG/Ldg1HmgaGT8KuKug/Mg0uj4EWJCa9BOBYekjzvsBw4CJad9CSUPSax1ZcK0WOeM0s5IoYx/nrsD3gWclzUhlvwDOA26VNAp4g+wTKgDuBfYDZgEfAj8AiIi5ks4FpqbjzomIuWn9BOD3QB0wIS2tcuA0s5IoVwdjRDxO63MBf2bCodTfeWIr17oWuLaF8mnA1u2tkwOnmZVEY9XOrpmfA6eZlUQtPXLpwGlmJVE7+aYDp5mViDNOM7OcqvVjMIrhwGlmJeHBITOznGonbDpwmlmJuI/TzCynWmqq+1l1M7OcnHGaWUnUTr7pwGlmJeI+TjOznGqpj9OB08xKonbCpgOnmZWIm+pmZjlFDeWcDpxmVhLOOM3McqqlwSHfAN8BrhrzG96e/TQznpq8vOzss37Kk9MnMW3q/Uy45yYGDFivjStYJZ1y8rE8PeNBZjw1mRtvuIzVV1+da66+kJdf+gvTpt7PtKn3s802W1W6mhUXRS7VSNnHc3Q+3boP7JwVK8Luu+3E4sVLuO66i9h2u+wjUnr1WpNFixYDcNKJR/PlL2/GiSedXslqWgs22GB9HnnoTr6yzV58/PHHjLvpSiZMeJBvfGNn7rn3Ae64455KV7HkGj6pL2qCuOM2+k5Rv7O/e/22qpuQzhlnB3js8b8yd978FcqagiZAz55r0Fn/gBl069aNuroedO3alTXq6pgz551KV6lTaixyqUYOnBV07jk/47VXpnLYYQdx1tm/rnR1rAVvv/0Ov73wSl57ZQqz33yKBQsXMumBR4Hs5/fk9En85tdn0b179wrXtPKiyH/VqMMDp6QfdPRrdlb/ccb5bPylrzNu3J2ceIK/LZ1R3759OGD/fdl0syEM+uL29Oy5BocffjD//sv/Yqut92DIzt+k31p9+befnlDpqlacM87yOru1HZJGS5omaVpj45KOrFNF3TTuDg46aL9KV8NaMHTo7rz2+pu8//5cGhoauPOPE9h5yA688857AHzyySeMHXsLX99huwrXtPJqKeMsy+1Ikp5pbRfQ6vBxRIwBxsDna3CoJZtuujGzZr0GwAH778tLL71S4RpZS956s56ddtqeuroefPTRx+y9125Mn/4066+/7vLgecABw5n5/IsVrmnlVWv2WIxy3ce5HrAvMK9ZuYA/l+k1O60bb7iMb+yxM/37r8Xrr07j7HMuYMSIvdlssy/R2NjIm2/Wc8KJHlHvjKZMfYo77riHqVMm0tDQwIwZM7nq6j9wz59upP86ayGJp5+e6Z8f0FhDA5xluR1J0jXAdRHxeAv7boqIw1d2jc97xmnWWRV7O9L3v3hwUb+zN7xxR9XdjlSWjDMiRrWxb6VB08yqTy1lOn7k0sxKopYeuXTgNLOSqNYR8mI4cJpZSXhU3cwsJzfVzcxyclPdzCwnN9XNzHKqpRm+HDjNrCTcx2lmlpOb6mZmOXlwyMwsp1pqqnsGeDMriYgoalkZSddKek/ScwVla0maJOnl9LVfKpekiyXNkvSMpO0LzjkqHf+ypKMKyr8m6dl0zsWSVjrpiAOnmZVEGWeA/z0wvFnZ6cDkiBgMTE7bACOAwWkZDVwBWaAFzgR2AnYEzmwKtumYYwvOa/5an+HAaWYlUa4Z4CPiUWBus+KRwNi0PhY4sKD8+sg8AfSVNIBsfuBJETE3IuYBk4DhaV/viHgisvT3+oJrtcp9nGZWEh3cx7leRMxJ6+/w6SdLDATeKjhudiprq3x2C+VtcsZpZhVV+FljaRmd5/yUKXZo1HbGaWYlUeyTQ4WfNZbDu5IGRMSc1Nx+L5XXA4MKjtswldUDezYrfziVb9jC8W1yxmlmJdFIFLUUaTzQNDJ+FHBXQfmRaXR9CLAgNeknAsMk9UuDQsOAiWnfQklD0mj6kQXXapUzTjMriXLdAC9pHFm22F/SbLLR8fOAWyWNAt4ADkmH3wvsB8wCPgR+ABARcyWdC0xNx50TEU0DTieQjdzXARPS0nadOuuD+f6wNrPKKPbD2vYYOLSo39lH6yf7w9rMrDbVUqbjwGlmJVFLj1w6cJpZSThwmpnl1FnHS8rBgdPMSsIZp5lZTp6P08wsJzfVzcxyclPdzCwnZ5xmZjk54zQzy8mDQ2ZmOTXWUFPd08qZmeXkjNPMSsJNdTOznGqpqe7AaWYl4YzTzCwnZ5xmZjk54zQzy8kZp5lZTs44zcxyimisdBU6jAOnmZWEn1U3M8vJsyOZmeXkjNPMLCdnnGZmOfl2JDOznHw7kplZTm6qm5nl5MEhM7OcatdBsG8AAARvSURBVCnj9AzwZmY5OeM0s5LwqLqZWU611FR34DSzkvDgkJlZTs44zcxych+nmVlOfnLIzCwnZ5xmZjm5j9PMLCc31c3McnLGaWaWkwOnmVlOtRM2QbX0V6IzkTQ6IsZUuh5WHP/8aptnR6qc0ZWugK0S//xqmAOnmVlODpxmZjk5cFaO+8eqm39+NcyDQ2ZmOTnjNDPLyYGzAiQNl/SSpFmSTq90faz9JF0r6T1Jz1W6LlY5DpwdTFJX4DJgBLAlcJikLStbK8vh98DwSlfCKsuBs+PtCMyKiFcj4hPgZmBkhetk7RQRjwJzK10PqywHzo43EHirYHt2KjOzKuHAaWaWkwNnx6sHBhVsb5jKzKxKOHB2vKnAYEkbS+oOHAqMr3CdzCwHB84OFhENwEnAROAF4NaImFnZWll7SRoH/AXYXNJsSaMqXSfreH5yyMwsJ2ecZmY5OXCameXkwGlmlpMDp5lZTg6cZmY5OXB+TkhaJmmGpOck3SZpjVW41u8lfTutX93WJCSS9pS0SxGv8bqk/u0tb3bM4pyvdZakn+Sto1lrHDg/Pz6KiG0jYmvgE+D4wp2Sivoo6Ig4JiKeb+OQPYHcgdOsmjlwfj49BmyassHHJI0HnpfUVdKvJU2V9Iyk4wCUuTTNEfoAsG7ThSQ9LGmHtD5c0pOSnpY0WdJGZAH61JTt7i5pHUm3p9eYKmnXdO7aku6XNFPS1YBW9iYk/VHS9HTO6Gb7LkzlkyWtk8q+JOm+dM5jkrYoxTfTrLmishDrvFJmOQK4LxVtD2wdEa+l4LMgIr4uaXXg/yTdD2wHbE42P+h6wPPAtc2uuw5wFbBHutZaETFX0pXA4oi4IB13E3BhRDwu6QtkT0h9GTgTeDwizpH0TaA9T9wcnV6jDpgq6faI+ADoCUyLiFMlnZGufRLZ5wAdHxEvS9oJuBzYu4hvo1mbHDg/P+okzUjrjwHXkDWhp0TEa6l8GPDVpv5LoA8wGNgDGBcRy4C3JT3YwvWHAI82XSsiWpuTch9gS2l5Qtlb0prpNQ5O594jaV473tPJkg5K64NSXT8AGoFbUvmNwB3pNXYBbit47dXb8RpmuTlwfn58FBHbFhakALKksAj4UURMbHbcfiWsRxdgSER83EJd2k3SnmRBeOeI+FDSw0CPVg6P9Lrzm38PzMrBfZy1ZSLwQ0mrAUjaTFJP4FHgu6kPdACwVwvnPgHsIWnjdO5aqXwR0KvguPuBHzVtSGoKZI8Ch6eyEUC/ldS1DzAvBc0tyDLeJl2Apqz5cLIugIXAa5K+k15DkrZZyWuYFcWBs7ZcTdZ/+WT6sLHfkbU67gReTvuuJ5v9ZwUR8XdgNFmz+Gk+bSr/CTioaXAIOBnYIQ0+Pc+no/tnkwXemWRN9jdXUtf7gG6SXgDOIwvcTZYAO6b3sDdwTio/AhiV6jcTfySJlYlnRzIzy8kZp5lZTg6cZmY5OXCameXkwGlmlpMDp5lZTg6cZmY5OXCameXkwGlmltP/B8bixiy5PuRMAAAAAElFTkSuQmCC\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_roc(\"Train base (NOT Undersampled)\", train_labels, train_predictions_undersampled_proba_t, color=colors[0])\n", | |
| "plot_roc(\"Test base (NOT Undersampled)\", test_labels, test_predictions_undersampled_proba_t, color=colors[0], linestyle='--')\n", | |
| "\n", | |
| "plot_roc(\"Train Undersampled 1:1\", train_labels, train_predictions_undersampled_t1_proba_t, color=colors[1])\n", | |
| "plot_roc(\"Test Undersampled 1:1\", test_labels, test_predictions_undersampled_t1_proba_t, color=colors[1], linestyle='--')\n", | |
| "\n", | |
| "plot_roc(\"Train Undersampled 1:7\", train_labels, train_predictions_undersampled_t2_proba_t, color=colors[2])\n", | |
| "plot_roc(\"Test Undersampled 1:7\", test_labels, test_predictions_undersampled_t2_proba_t, color=colors[2], linestyle='--')\n", | |
| "\n", | |
| "plt.legend(loc='lower right');\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 606 | |
| }, | |
| "id": "dEN8MX5UpGwc", | |
| "outputId": "1346f5ee-dd45-429f-f280-afcde34a6d1d" | |
| }, | |
| "execution_count": 31, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "plot_prc(\"Train base (NOT Undersampled)\", train_labels, train_predictions_undersampled_proba_t, color=colors[0])\n", | |
| "plot_prc(\"Test base (NOT Undersampled)\", test_labels, test_predictions_undersampled_proba_t, color=colors[0], linestyle='--')\n", | |
| "\n", | |
| "plot_prc(\"Train Undersampled 1:1\", train_labels, train_predictions_undersampled_t1_proba_t, color=colors[1])\n", | |
| "plot_prc(\"Test Undersampled 1:1\", test_labels, test_predictions_undersampled_t1_proba_t, color=colors[1], linestyle='--')\n", | |
| "\n", | |
| "plot_prc(\"Train Undersampled 1:7\", train_labels, train_predictions_undersampled_t2_proba_t, color=colors[2])\n", | |
| "plot_prc(\"Test Undersampled 1:7\", test_labels, test_predictions_undersampled_t2_proba_t, color=colors[2], linestyle='--')\n", | |
| "\n", | |
| "plt.legend(loc='lower right');" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 606 | |
| }, | |
| "id": "Mqfz0fC0pl0O", | |
| "outputId": "799f5944-da1b-458e-e754-68d1738ba171" | |
| }, | |
| "execution_count": 32, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 864x720 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "y-D8_7MiJMyR" | |
| }, | |
| "execution_count": 32, | |
| "outputs": [] | |
| } | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "provenance": [], | |
| "include_colab_link": true | |
| }, | |
| "kernelspec": { | |
| "display_name": "Python 3", | |
| "name": "python3" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 0 | |
| } |
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