María Jesús Ugarte mjesusugarte
mjesusugarte
/ picp.py
Created
March 5, 2021 14:21
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| def picp(real, lower, upper): | |
| return ((real <= upper) & (real >= lower)).mean() |
mjesusugarte
/ nonconformist_interval.py
Created
March 5, 2021 12:57
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| from nonconformist.cp import IcpRegressor | |
| from nonconformist.cp import IcpClassifier | |
| from nonconformist.nc import NcFactory | |
| import lightgbm as lgbm | |
| # Create the underlying model | |
| model = lgbm.LGBMRegressor() | |
| # Default nonconformity measure | |
| nc = NcFactory.create_nc(model) | |
| # Inductive conformal regressor | |
| icp = IcpRegressor(nc) |
mjesusugarte
/ preprocessing_nonconformist.py
Created
March 5, 2021 12:54
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| target_column_name = 'charges' | |
| train_percentage = 0.7 | |
| cal_percentage = 0.2 | |
| X = df.drop(columns=target_column_name).to_numpy() | |
| Y = df[target_column_name].to_numpy() | |
| n_total = X.shape[0] | |
| n_train = int(train_percentage*n_total) | |
| n_cal = int(cal_percentage*n_total) + n_train | |
| train_data = X[:n_train, :] | |
| train_target = Y[:n_train] |