evalKerasTransferLearning: evalKerasTransferLearning

In SPOTMisc: Misc Extensions for the 'SPOT' Package

evalKerasTransferLearning

Description

Hyperparameter Tuning: Keras TransferLearning Test Function.

Usage

evalKerasTransferLearning(x, kerasConf = getKerasConf(), data = NULL)

Arguments

x	matrix of hyperparameter values to evaluate with the function. Rows for points and columns for dimension. "dropout" = x[1], "learning_rate" = x[2], "epochs" = x[3], "beta_1" = x[4], "beta_2" = x[5], "epsilon" = x[6], and "optimizer" = x[7] (type: factor).
kerasConf	List of additional parameters passed to keras as described in getKerasConf. Default: kerasConf = getKerasConf().
data	data

Details

Trains a transfer learning model. Standard Code from https://tensorflow.rstudio.com/ Modified by T. Bartz-Beielstein ([e-mail])

Value

list with function values (training, validation, and test loss/accuracy, and keras model information)

See Also

getKerasConf

funKerasTransferLearning

funKerasMnist

fit

Examples

### These examples require an activated Python environment as described in
### Bartz-Beielstein, T., Rehbach, F., Sen, A., and Zaefferer, M.:
### Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT,
### June 2021. http://arxiv.org/abs/2105.14625.
PYTHON_RETICULATE <- FALSE
if(PYTHON_RETICULATE){

library("SPOTMisc")
lower <- c(1e-6, 1e-6, 1, 0.6, 0.99, 1e-9, 1)
x <- matrix(lower, 1,)
res <- evalKerasTransferLearning(x,
                                 kerasConf = getKerasConf()
                                 )
str(res)
### The number of units for all layers can be listed as follows:
res$modelConf$config$layers[,2]$units
}

SPOTMisc documentation built on Sept. 5, 2022, 5:06 p.m.