Neural Networks with R

Autoencoders using H2O

An autoencoder is an ANN used for learning without efficient coding control. The purpose of an autoencoder is to learn coding for a set of data, typically to reduce dimensionality. Architecturally, the simplest form of autoencoder is an advanced and non-recurring neural network very similar to the MLP, with an input level, an output layer, and one or more hidden layers that connect them, but with the layer outputs having the same number of input level nodes for rebuilding their inputs.

In the following is proposed an example of autoencoder using h2o on a movie dataset.

The dataset used in this example is a set of movies and genre taken from https://grouplens.org/datasets/movielens.

We use the movies.csv file, which ...