Simple overview of use/purpose.
An in-depth paragraph about your project and overview of use.
| #sklearn.metrics has a mean_squared_error function. The RMSE is just the square root of whatever it returns. | |
| #source:https://intellipaat.com/community/1269/is-there-a-library-function-for-root-mean-square-error-rmse-in-python | |
| from sklearn.metrics import mean_squared_error | |
| from math import sqrt | |
| rms = sqrt(mean_squared_error(y_actual, y_predicted)) |
| # See http://help.github.com/ignore-files/ for more about ignoring files. | |
| # compiled output | |
| /dist | |
| /tmp | |
| /out-tsc | |
| # Runtime data | |
| pids | |
| *.pid |