fineTuneDArch-DArch-method: Fine tuning function for the deep architecture

In maddin79/darch: Package for Deep Architectures and Restricted Boltzmann Machines

Description

Fine tuning function for the deep architecture

Usage

## S4 method for signature 'DArch'
fineTuneDArch(darch, dataSet, dataSetValid = NULL,
  numEpochs = 1, isClass = TRUE, stopErr = -Inf, stopClassErr = 101,
  stopValidErr = -Inf, stopValidClassErr = 101,
  shuffleTrainData = getParameter(".shuffleTrainData", T),
  debugMode = getParameter(".debug", F), ...)

Arguments

darch	A instance of the class DArch.
dataSet	DataSet containing training and optionally validation and test data.
dataSetValid	DataSet to be used for validation.
numEpochs	The number of training iterations
isClass	Indicates whether the training is for a classification net. When TRUE then statistics for classification will be determind. Default is TRUE
stopErr	Stop criteria for the error on the train data. Default is -Inf
stopClassErr	Stop criteria for the classification error on the train data. Default is 101
stopValidErr	Stop criteria for the error on the validation data. Default is -Inf.
stopValidClassErr	Stop criteria for the classification error on the validation data. Default is 101.
shuffleTrainData	Whether to shuffle train data before each epoch.
debugMode	Whether to enable debug mode, internal parameter.
...	Additional parameters for the training function

See Also

fineTuneDArch

maddin79/darch documentation built on May 21, 2019, 10:53 a.m.