R Deep Learning Cookbook by Dr. PKS Prakash

Author:Dr. PKS Prakash
Language: eng
Format: epub
Tags: COM044000 - COMPUTERS / Neural Networks, COM004000 - COMPUTERS / Intelligence (AI) and Semantics, COM042000 - COMPUTERS / Natural Language Processing
Publisher: Packt
Published: 2017-08-04T08:48:03+00:00

require(SAENET)

Load the train and test occupancy dataset using load_occupancy_data:

occupancy_train <-load_occupancy_data(train=T)

occupancy_test <- load_occupancy_data(train = F)

Normalize the dataset using the minmax.normalize function:

# Normalize dataset

occupancy_train<-minmax.normalize(occupancy_train, scaler = NULL)

occupancy_test<-minmax.normalize(occupancy_test, scaler = occupancy_train$scaler)

The stacked autoencoder model can be built using the SAENET.train train function from the SAENET package:

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