tree_reg: Custom function for regression by decision tree.

In AbirChakraborty1/RegFunction: custom function for regression models

Description

This function takes training data, tesing data, target variable and predict target variable of the training data

Usage

tree_func(train, test, target, drop = NULL)

Arguments

train	Training Data as a dataframe.
test	Testing Data as a dataframe.
target	Name of the variable where probability score needs to be predicted
drop	Name of the variable that needs to be dropped before building the model.

Details

This is a custom function for regression by decision tree, it builds a tree model first on the training data.

The argument 'drop' removes the variables not needed to build the model.

The remaining variables are used to make the final tree model and predict the target variable on the training data.

Value

The value returns from this function is a numeric vector.

Author(s)

ABIR CHAKRABORTY < [e-mail] >

AbirChakraborty1/RegFunction documentation built on Feb. 25, 2022, 12:22 p.m.