raredecay.tools.estimator module

Created on Sat May 21 12:02:58 2016

@author: Jonas Eschle “Mayou36”

class raredecay.tools.estimator.Mayou(base_estimators=None, bagging_base=None, stacking='xgb', features_stack=None, bagging_stack=None, hunting=False, transform=True, transform_pred=True)

Bases: rep.estimators.interface.Classifier

Classifier for raredecay analysis

blablabla

Parameters:base_estimators (dict('clf': classifier OR keyword-parameters)) –

Contains all the level-0 classifiers. The key is the name of the classifier and the value is either a prefitted classifier or a dictionary containing the keyword arguments to instantiate such a classifier.

If no pre-trained classifier is provided, the key-value has to be one of the following:

• ‘xgb’ creates an XGBoost classifier
• ‘rdf’ creates a Random Forest classifier
• ‘erf’ creates a Forest consisting of Extra Randomized Trees
• ‘nn’ creates an artificial Neural Network from TheaNets
• ‘ada’ creates an AdaBoost instance with Decision Trees as basis
• ‘gb’ creates a Gradient Boosted classifier with Decision Trees as basis

fit(X, y, sample_weight=None)

get_params(deep=True)

predict(X)

predict_proba(X)

stacker_test_on(X, y, sample_weight=None)

Return report for the stacker only

stacker_test_on_lds(lds)

Return report for the stacker only

staged_predict_proba(X)

test_on(X, y, sample_weight=None)

test_on_lds(lds)