Understanding Deep Learning Applications in Rare Event Prediction/

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Autoencoders as Neural Network Version of PCA

Autoencoders as Neural Network Version of PCA

Exploring autoencoders as a neural network version of PCA for dimension reduction and feature representation.

We'll cover the following...

Background

An autoencoder is a reconstruction model. It attempts to reconstruct its inputs from itself as depicted below:

x→f(x)→z⏟encoding→g(z)→x^⏟decoding.x → \underbrace{f(x) → z}_{\text{encoding}} → \underbrace{g(z) → \hat{x}}_{\text{decoding}}.

An autoencoder is made of two modules: encoder and decoder.

As their names indicate, an encoder ff encodes input ...