A Novel Framework Using Deep Auto-Encoders Based Linear Model for Data Classification

A Novel Framework Using Deep Auto-Encoders Based Linear Model for Data Classification

This paper proposes a novel data classification framework, combining sparse auto-encoders (SAEs) and a post-processing system consisting of a linear system model relying on Particle Swarm Optimization (PSO) algorithm. All the sensitive and high-level features are extracted by using the first auto-en...

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Bibliographic Details
Main Authors: Ahmad M. Karim, Hilal Kaya, Mehmet Serdar Güzel, Mehmet R. Tolun, Fatih V. Çelebi, Alok Mishra
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
deep sparse auto-encoders
medical diagnosis
linear model
data classification
PSO algorithm
Online Access:https://www.mdpi.com/1424-8220/20/21/6378

Internet

https://www.mdpi.com/1424-8220/20/21/6378

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