R/d1.dl.R

In overhuman/d1r: d1r package

d1.dl.RBM.fit <- function(DT){



	...



}


d1.dl.RBMstack.fit <- function(f,DT,bin=F){

	return(darch(
				 darch.bootstrap = F,
				 darch.fineTuneFunction = "backpropagation",
				 darch.isBin = bin,
				 darch.numEpochs = 100,
				 rbm.numEpochs = 0, #pretrain
				 layers = c(33,40,4,50,2),
				 rbm.allData = F,
				 rbm.batchSize = 3,
				 bp.learnRat = 0.1,
				 normalizeWeights = T,
				 normalizeWeightsBound = 5, 
				 darch.dropout = 0.2, 
				 darch.dither = T, 
				 darch.weightDecay = 0.0001
				 )
	)

}

d1.dl.RBMstack.predict <- function(test,model,y){

	if (bin==T){

		predictions <- predict(darch, type="bin")
		numCorrect <- sum(predictions == test[,eval(parse(text=y))])
		cat(paste0("Correct classifications on all data: ", numCorrect,
				   " (", round(numCorrect/nrow(trainTargets)*100, 2), "%)\n"))
	} else {
		predictions <- predict(model, type="bin")
	}
}