Autoencoder Feature Selector basic example

Version 3.0.0 (3.25 KB) by Lyes Demri
This code implements the method described in "Autoencoder Inspired Unsupervised Feature" (Han 2018)
5 Downloads
Updated 22 Apr 2024

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This code implements the method described in "Autoencoder Inspired Unsupervised Feature" (Han 2018). Four 3x3 pixel images are generated, then an autoencoder is trained with Row-Sparse Regularization on the encoder and Sparsity Regularization. The AE is tested by attempting to denoise noisy images. It can be seen that regularization provides smaller weights and biases for the network, but at the cost of a worse reconstruction.

Cite As

Lyes Demri (2024). Autoencoder Feature Selector basic example (https://www.mathworks.com/matlabcentral/fileexchange/162171-autoencoder-feature-selector-basic-example), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2024a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
3.0.0

Added necessary functions

2.0.0

*Used larger images
*Implemented feature selection logic and feature weight visualization

1.0.0