deeplearning-methods:
Create deeplearning objects from training set.
Description
Rda, Rsda, Rrbm and Rdbn will return an instantiated deeplearning object
for denoising autoencoder, stacked denoising autoencoder, restricted Boltzmann machine and deep belief net.
train and reconstruct are for training and reconstructing from denoising autoencoder and restricted Boltzmann machine;
pretrain, finetune and predict are used for pretraining, finetuning and predicting
using stacked denoising autoencoder and deep belief net.
Usage
Rda(x) Rsda(x, y, hidden) Rrbm(x) Rdbn(x, y, hidden) train(object) pretrain(object) finetune(object) reconstruct(object, test) predict(object, test)
Arguments
y
The labels for training dataset.
hidden
The number of hidden representation in each layer.
object
An instantiated deeplearning object.
Examples
data(test)
dbn_test <- Rdbn(train_X, train_Y, hidden)
summary(dbn_test)
LearningRate(dbn_test)
pretrain(dbn_test)
finetune(dbn_test)
predict(dbn_test, test_X)