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glmtree (version 0.2)

Logistic Regression Trees

Description

A logistic regression tree is a decision tree with logistic regressions at its leaves. A particular stochastic expectation maximization algorithm is used to draw a few good trees, that are then assessed via the user's criterion of choice among BIC / AIC / test set Gini. The formal development is given in a PhD chapter, see Ehrhardt (2019) .

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Version

Install

install.packages('glmtree')

Monthly Downloads

22

Version

0.2

License

GPL (>= 2)

Maintainer

Adrien Ehrhardt

Last Published

October 3rd, 2020

Functions in glmtree (0.2)

generateData

Generates data from two logistic regression trees.
glmdisc-class

Class glmtree
predict_tweaked

Tweaked predict to take into account levels that are not in the training set but in the test set and remove these rows.
normalizedGini

Calculating the normalized Gini index
initialization

Random initialization of the segmentation
glmtree

Logistic regression tree by Stochastic-Expectation-Maximization