toad.scorecard module

class toad.scorecard.ScoreCard(pdo=60, rate=2, base_odds=35, base_score=750, **kwargs)

Bases: sklearn.base.BaseEstimator

bin_to_score(bins, return_sub=False)

predict score from bins

combine(X)

export(to_frame=False, to_json=None, to_csv=None, decimal=2)

generate a scorecard object

Parameters:

• to_frame (bool) – return DataFrame of card
• to_json (str|IOBase) – io to write json file
• to_csv (filepath|IOBase) – file to write csv

Returns:

dict

fit(X, y, combiner=None, transer=None, model=None)

Parameters:

• X (2D array-like) –
• Y (array-like) –

generate_card(card=None, combiner={}, transer=None, model=None)

Parameters:

• card (dict|str|IOBase) – dict of card or io to read json
• combiner (toad.Combiner) –
• transer (toad.WOETransformer) –
• model (LogisticRegression) –

generate_map(transer, model)

calculate score map by woe

predict(X, **kwargs)

predict score :param X: X to predict :type X: 2D array-like :param return_sub: if need to return sub score, default False :type return_sub: bool

Returns:predicted score DataFrame: sub score for each feature Return type:array-like

proba_to_score(prob)

covert probability to score

set_card(card)

set card dict

set_combiner(combiner)

set combiner

set_model(model)

set logistic regression model

set_score(map)

set score map by dict

testing_frame(**kwargs)

get testing frame with score

Returns:testing frame with score Return type:DataFrame

woe_to_score(woe, weight=None)

calculate score by woe