predict.dblr

A fitted dblr model object, which should be returned by calling dblr_train function

object

A data.frame contains the samples to predict

newdata

Control the output of prediction. Default: 'response' means probability; 'Link' would produce the linear part; 'mapped' would produce a data.frame filling with the coefficients of the model

type

further arguments passed to or from other methods

predict.dblr makes predictions on new data set given the fitted dblr model object.

Trains logistic regression model by discretizing continuous variables via gradient boosting approach. The proposed method tries to achieve a tradeoff between interpretation and prediction accuracy for logistic regression by discretizing the continuous variables. The variable binning is accomplished in a supervised fashion. The model trained by this package is still a single
logistic regression model, but not a sequence of logistic regression models. The fitted model
object returned from the model training consists of two tables. One table is used to give the
boundaries of bins for each continuous variable as well as the corresponding coefficients,
and the other one is used for discrete variables. This package can also be used for binning
continuous variables for other statistical analysis.

predict.dblr: Discrete Boosting Logistic Regression Prediction

Description

Usage

Arguments

Value