Credit Scorecard Modelling Utils


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Documentation for package ‘scorecardModelUtils’ version 0.0.1.0

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categorical_iv IV table for individual categorical variable
cat_new_class Clubbing class of categorical variables with low population percentage with another class of similar event rate
club_cat_class Clubbing class of a categorical variable with low population percentage with another class of similar event rate
cv_filter Variable reduction based on Cramer's V filter
cv_table Pairwise Cramer's V among a list of categorical variables
cv_test Cramer's V value between two categorical variables
dtree_split_val Getting the split value for terminal nodes from decision tree
dtree_trend_iv Recursive Decision Tree partitioning with monotonic event rate along with IV table for individual numerical variable
fn_conf_mat Creates confusion matrix and its related measures
fn_cross_index Creates random index for k-fold cross validation
fn_error Computes error measures between observed and predicted values
fn_mode Calculating mode value of a vector
fn_target Redefines target value
gini_table Performance measure table with Gini coefficient, KS-statistics and Gini lift curve
gradient_boosting_parameters Hyperparameter optimisation or parameter tuning for Gradient Boosting Regression Modelling by grid search
iv_filter Variable reduction based on Information Value filter
iv_table WOE and IV table for list of numerical and categorical variables
missing_val Missing value imputation
num_to_cat Binning numerical variables based on cuts from IV table
others_class Clubbing of classes of categorical variable with low population percentage into one class
random_forest_parameters Hyperparameter optimisation or parameter tuning for Random Forest by grid search
sampling Random sampling of data into train and test
scalling Converting coefficients of logistic regression into scores for scorecard building
scoring Scoring a dataset with class based on a scalling logic to arrive at final score
support_vector_parameters Hyperparameter optimisation or parameter tuning for Suppert Vector Machine by grid search
univariate Univariate analysis of variables
vif_filter Removing multicollinearity from a model using vif test