Models¶
Here are some examples to get you started.
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src.models.train_model.
model_ensembler
(X_train_tfv, X_train_ft, y_train)¶ Train ensemble model
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src.models.train_model.
model_lightgbm
(X_train, y_train)¶ Light Gradient Boosting Machine
https://github.com/Microsoft/LightGBM/blob/master/docs/Features.rst
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src.models.train_model.
model_ridge
(X_train, y_train)¶ Ridge regression Minimizing the residual sum of squares we also have a penalty on the coefficients
http://scikit-learn.org/stable/modules/linear_model.html#ridge-regression
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src.models.train_model.
model_xgb
(X_train, y_train)¶ Extreme gradient boosting
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src.models.train_model.
score_function
(y_true, y_pred)¶ Score function auc
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src.models.train_model.
split_train
(X, y, test_size, random_state=7)¶ Train and validation split