We hold a WeChat group for questions and suggestions. fit ( final_data, final_data ) print ( card. ScoreCard ( combiner = c, transer = transer, class_weight = 'balanced', C = 0.1, base_score = 600, base_odds = 35, pdo = 60, rate = 2 ) card. KS_bucket ( pred_proba, final_data, bucket = 10, method = 'quantile' )Ĭard = toad. transform ( data_selected ], labels = True ), x = col, target = 'target' ) export ()) # Visualisation to check binning results col = 'feature_name' bin_plot ( c. drop ( to_drop, axis = 1 ), y = 'target', method = 'chi', min_samples = 0.05 ) print ( c. Reliable fine binning with visualisation.stepwise ( data_woe, target = 'target', estimator = 'ols', direction = 'both', criterion = 'aic', exclude = to_drop ) select ( data, target = 'target', empty = 0.5, iv = 0.02, corr = 0.7, return_drop = True, exclude = ) final_data = toad. Experience deep functionality, extensive automation, and workflows that will help you work more accurately. and stepwise feature selection (with optimised algorithm) Start your free 30-day trial today Toad for Oracle helps Oracle developers get their jobs done faster If you hate dealing with manual and repetitive tasks and want to work more efficiently, Toad is for you.Preliminary selection based on criteria.quality ( data, 'target', iv_only = True ) Simple IV calculation for all features. The following showcases some of the most popular features of toad, for more detailed demonstrations and user guidance, please refer to the tutorials. Its key functionality streamlines the most critical and time-consuming process such as feature selection and fine binning. to results validation and scorecard transformation. It provides intuitive functions of the entire process, from EDA, feature engineering and selection etc. Toad is dedicated to facilitating model development process, especially for a scorecard.
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