Feature Transformation Framework for Enhancing Compactness and Separability of Data Points in Feature Space for Small Datasets

Feature Transformation Framework for Enhancing Compactness and Separability of Data Points in Feature Space for Small Datasets

Compactness and separability of data points are two important properties that contribute to the accuracy of machine learning tasks such as classification and clustering. We propose a framework that enhances the goodness criteria of the two properties by transforming the data points to a subspace in...

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Bibliographic Details
Main Authors: Mahmoud Maher ElMorshedy, Radwa Fathalla, Yasser El-Sonbaty
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Applied Sciences
Subjects:
compactness
separability
feature space
feature mapping
small datasets
autoencoder
Online Access:https://www.mdpi.com/2076-3417/12/3/1713

Internet

https://www.mdpi.com/2076-3417/12/3/1713

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