# Discretization and Grouping for Logistic Regression

## Documentation for package ‘glmdisc’ version 0.6

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

glmdisc-package | glmdisc: A package for discretizing continuous features, grouping categorical features' values and optimizing it for logistic regression.
cutpoints | Obtaining the cutpoints and / or regroupments of a discretization.
cutpoints-method | Obtaining the cutpoints and / or regroupments of a discretization.
discretize | Prediction on a raw test set of the best logistic regression model on discretized / grouped data.
discretize-method | Prediction on a raw test set of the best logistic regression model on discretized / grouped data.
glmdisc | Model-based multivariate discretization for logistic regression.
glmdisc-class | Class glmdisc
normalizedGini | Calculating the normalized Gini index
plot | Plots for the discretized / grouped data.
plot-method | Plots for the discretized / grouped data.
plot.glmdisc | Plots for the discretized / grouped data.
predict | Prediction on a raw test set of the best logistic regression model on discretized data.
predict-method | Prediction on a raw test set of the best logistic regression model on discretized data.
predict.glmdisc | Prediction on a raw test set of the best logistic regression model on discretized data.
predictlogisticRegression | Predicting using a logistic regression fitted with RCpp::fast_LR.