Hybrid stacked sparse autoencoder for robust feature extraction and classification in sparse data across multiple domains

Tabular data is the most used data format in applied mathematics, cybersecurity, finance, and healthcare, and it presents distinct issues due to its intrinsic sparsity, with the majority of values being zero. These factors inhibit effective feature selection and reduce prediction accuracy. The Stack...

Full description

Bibliographic Details

Published in:	Machine learning with applications Vol. 22; p. 100764
Main Authors:	Abdussamad, Abdulkadir, Said Jadid, Daud, Hanita, Sokkalingam, Rajalingam, Khan, Iliyas Karim
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.12.2025
Subjects:	Autoencoder Binary classification High-dimensional data Hybrid stacked sparse autoencoder Sparse data High-dimensional data Sparse data Hybrid stacked sparse autoencoder Autoencoder Binary classification
ISSN:	2666-8270, 2666-8270
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!