LRBoost is a combination of a linear estimator and gradient boosting that is scikit-learn compatible.
LRBoostRegressor can be used like any other sklearn estimator and is built off a sklearn template.
predictreturns an array-like of final predictionspredict_detailreturns a dictionary with the linear, non-linear, and final predictions.predict(X)andpredict_detail(X)['pred']are equivalent values>>> from sklearn.datasets import load_iris >>> from lrboost import LRBoostRegressor >>> X, y = load_iris(return_X_y=True) >>> lrb = LRBoostRegressor.fit(X, y) >>> predictions = lrb.predict(X) >>> detailed_predictions = lrb.predict_detail(X)
More detailed documentation can be found here -> https://readthedocs.org/projects/lrboost.
Andrew Patton & Kostya Medvedovsky