training_data_checker-honestRF: training_data_checker-hoenstRF

Description Usage Arguments

Description

Check the input to honestRF constructor

Usage

1
2
training_data_checker(x, y, ntree, replace, sampsize, mtry, nodesizeSpl,
  nodesizeAvg, splitratio, nthread, middleSplit)

Arguments

x

A data frame of all training predictors.

y

A vector of all training responses.

ntree

The number of trees to grow in the forest. The default value is 500.

replace

An indicator of whether sampling of training data is with replacement. The default value is TRUE.

sampsize

The size of total samples to draw for the training data. If sampling with replacement, the default value is the length of the training data. If samplying without replacement, the default value is two-third of the length of the training data.

mtry

The number of variables randomly selected at each split point. The default value is set to be one third of total number of features of the training data.

nodesizeSpl

The minimum observations contained in terminal nodes. The default value is 3.

nodesizeAvg

Minimum size of terminal nodes for averaging dataset. The default value is 3.

splitratio

Proportion of the training data used as the splitting dataset. It is a ratio between 0 and 1. If the ratio is 1, then essentially splitting dataset becomes the total entire sampled set and the averaging dataset is empty. If the ratio is 0, then the splitting data set is empty and all the data is used for the averaging data set (This is not a good usage however since there will be no data available for splitting).

nthread

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

middleSplit

if the split value is taking the average of two feature values. If false, it will take a point based on a uniform distribution between two feature values. (Default = FALSE)


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