ensembleControl: ensembleControl

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02/28/2023

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.

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