rusboost: RUSBoost for two-class problems

View source: R/rusboost.R

rusboostR Documentation

RUSBoost for two-class problems

Description

RUSBoost for two-class problems

Usage

rusboost(formula, df, size, ir = 1, learn_rate = 1, rus = TRUE, control)

Arguments

formula

A formula specify predictors and target variable. Target variable should be a factor of 0 and 1. Predictors can be either numerical and categorical.

df

A df frame used for training the model, i.e. training set.

size

Ensemble size, i.e. number of weak learners in the ensemble model

ir

Imbalance ratio. Specifies how many times the under-sampled majority instances are over minority instances.

learn_rate

Default of 1.

rus

TRUE for random undersampling; FALSE for AdaBoost with full sample

control

Control object passed onto rpart function.

Value

rusboost object


farr documentation built on May 29, 2024, 6:41 a.m.