deepboost (version 0.1.5)

deepboost.formula: Main function for deepboost model creation, using a formula

Description

Main function for deepboost model creation, using a formula

Usage

deepboost.formula(formula, data, instance_weights = NULL, tree_depth = 5, num_iter = 1, beta = 0, lambda = 0.05, loss_type = "l", verbose = TRUE)

Arguments

formula

A R Formula object see : ?formula

data

A data.frame of samples to train on

instance_weights

The weight of each example

tree_depth

maximum depth for a single decision tree in the model

num_iter

number of iterations = number of trees in ensemble

beta

regularisation for scores (L1)

lambda

regularisation for tree depth

loss_type

- "l" logistic, "e" exponential

verbose

- print extra data while training TRUE / FALSE

Value

A trained Deepbost model

Examples

deepboost.formula(y ~ .,
 data.frame(x1=rep(c(0,0,1,1),2),x2=rep(c(0,1,0,1),2),y=factor(rep(c(0,0,0,1),2))),
 num_iter=1)
deepboost.formula(y ~ .,
 data.frame(x1=rep(c(0,0,1,1),2),x2=rep(c(0,1,0,1),2),y=factor(rep(c(0,0,0,1),2))),
 num_iter=2, beta=0.1, lambda=0.00125)