extractGenericJuice: extractGenericJuice

Description Usage Arguments Value

View source: R/hello.R

Description

Returns cross validation data from folds (i.e. if 2 folds, then aggregate the data on fold 2 after training only on fold 1 & the data on fold 1 after training only on fold 2). This is helps in feature engineering.

Usage

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extractGenericJuice(X_train, Y_train, numFolds, parCV, numCores, seedNum,
  verbose_p, fn, fn_params)

Arguments

X_train

Training Data (excludes the response/target we wish to predict ) that will be fed into the pipeline function.

Y_train

Training Response/Target - The response/target that will be fed into the pipeline function.

numFolds

Integer indicating the number of folds to use to extract data

parCV

Boolean indicating whether to parallelize the extraction prodcedure.

numCores

Integer indicating the number of cores to use when generating predictions.

seedNum

Integer indicating the seed number. Using the same seed will generate the same folds.

verbose_p

Boolean indicating if prediction extraction details should be printed out the screen.

fn

The pipeline function. The pipeline function must take parameters training data, training response, validation data, validation response. See examples for details.

fn_params

Additional parameters to supply to the pipeline function. See examples for details.

Value

CV Fold Predictions


sjoshistrats/JuiceBox documentation built on May 30, 2019, 12:05 a.m.