jarvis.ai.pkgs.lgbm.regression
¶
Modules for LightGBM regression.
Module Contents¶
Functions¶
|
Get generic regression model. |
|
Train a lightgbm model. |
Give example optimized parameters. |
Attributes¶
- jarvis.ai.pkgs.lgbm.regression.regression(X=[], Y=[], jid=[], test_size=0.1, plot=False, preprocess=True, feature_importance=True, save_model=False, feat_names=[], model_name='my_model', config={})[source]¶
Get generic regression model.
- jarvis.ai.pkgs.lgbm.regression.default_param_dist¶
- jarvis.ai.pkgs.lgbm.regression.get_lgbm(train_x, val_x, train_y, val_y, cv, n_jobs, scoring, n_iter, objective, alpha, random_state, param_dist=default_param_dist)[source]¶
Train a lightgbm model.
Args:
train_x: samples used for trainiing
val_x: validation set
train_y: train targets
val_y: validation targets
cv: # of cross-validations
n_jobs: for making the job parallel
scoring: scoring function to use such as MAE
- Returns:
Best estimator.