logit.boost: Implementation of the Binary LogitBoost Algorithm

In Accelerytics/mlkit: Machine Learning Kit

Description

Implementation of the LogitBoost algorithm based on Friedman, J., Hastie, T., and Tibshirani, R. (2000)

Usage

logit.boost(formula, data, n.iter)

Arguments

formula	an object of class formula: a symbolic description of the model to be fitted following the standard of lm.
data	an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment (formula), typically the environment from which this function is called.
n.iter	number of iterations to apply.

Value

logic.boost returns an object of class mlkit.class.fit. An object of class mlkit.class.fit is a list containing at least the following components:

classifier	a multiclass classifier function.
y.hat	the in-sample classifications of the given data.

Accelerytics/mlkit documentation built on Dec. 31, 2020, 9:46 a.m.