ensembleControl: ensembleControl

Control the parameters used to create an ensemble.

Usage

  ensembleControl(randomSeed = NULL, modelCount = 1, replace = FALSE,
    sampRate = ifelse(replace, 1, 0.632), splitData = FALSE,
    combineMethod = NULL, ...)
 

Arguments

randomSeed

Specifies the random seed. The default value is NULL.

modelCount

Specifies the number of models to train. The default value is 1, meaning no ensembling occurs.

replace

A logical value specifying if the sampling of observations should be done with or without replacement. The default value is FALSE.

sampRate

a scalar of positive value specifying the percentage of observations to sample for each trainer. The default is 1.0 for sampling with replacement (i.e., replace=TRUE) and 0.632 for sampling without replacement (i.e., replace=FALSE).

splitData

A logical value that specifies whether or not to train the base models on non-overlapping partitions. The default is FALSE. It is available only for RxSpark compute context and is ignored for others.

combineMethod

Specifies the method used to combine the models:

• median to compute the median of the individual model outputs,
• average to compute the average of the individual model outputs and
• vote to compute (pos-neg) / the total number of models, where 'pos' is the number of positive outputs and 'neg' is the number of negative outputs. The default value is median.

...

Not used currently.

Value

A list of ensemble parameters.