Autoencoder Feature Selector basic example

Version 3.0.0 (3,25 KB) von Lyes Demri
This code implements the method described in "Autoencoder Inspired Unsupervised Feature" (Han 2018)
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Aktualisiert 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.

Zitieren als

Lyes Demri (2026). Autoencoder Feature Selector basic example (https://de.mathworks.com/matlabcentral/fileexchange/162171-autoencoder-feature-selector-basic-example), MATLAB Central File Exchange. Abgerufen.

Kompatibilität der MATLAB-Version
Erstellt mit R2024a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux
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Version Veröffentlicht Versionshinweise
3.0.0

Added necessary functions

2.0.0

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

1.0.0