autohonestRF-honestRF: autohonestRF-honestRF

Description Arguments Format

Description

Autotune a honestRF based on the input dataset. The methodology is based on paper 'Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization' by Lisha Li, et al.

Arguments

x

A data frame of all training predictors.

y

A vector of all training responses.

sampsize

The size of total samples to draw for the training data.

num_iter

Maximum iterations/epochs per configuration. Default is 1024.

eta

Downsampling rate. Default value is 2.

verbose

if tuning process in verbose mode

seed

random seed

nthread

Number of threads to train and predict thre forest. The default number is 0 which represents using all cores.

Format

An object of class NULL of length 0.


soerenkuenzel/hte documentation built on June 12, 2018, 4:26 p.m.