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Expand file tree Collapse file tree Original file line number Diff line number Diff line change 88Main Features
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11- * Prepare a given pandas DataFrame for predictive modelling:
12- - partition into train/selection/validation sets
13- - create bins from continuous variables
14- - regroup categorical variables based on statistical significance
15- - replace missing values and
16- - add columns with incidence rate per category/bin.
17- * Perform univariate feature selection based on AUC
18- * Compute correlation matrix of predictors
19- * Find the suitable variables using forward feature selection
20- * Evaluate model performance and visualize the results
11+ - Prepare a given pandas DataFrame for predictive modelling:
12+
13+ - partition into train/selection/validation sets
14+ - create bins from continuous variables
15+ - regroup categorical variables based on statistical significance
16+ - replace missing values and
17+ - add columns with incidence rate per category/bin
18+
19+ - Perform univariate feature selection based on AUC
20+ - Compute correlation matrix of predictors
21+ - Find the suitable variables using forward feature selection
22+ - Evaluate model performance and visualize the results
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2224Getting started
2325===============
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