Feb 20, 2013 · Effective Feature Subset Selection (FSS) is an important step when designing engineering systems that classify complex data in real time.
Abstract. Effective Feature Subset Selection (FSS) is an important step when designing engineering systems that classify complex data in real time.
Effective Feature Subset Selection (FSS) is an important step when designing engineering systems that classify complex data in real time.
This work proposes the use of Thornton's Separabilit y Index as a simple measure of subset merit which is fast and easy to calculate, but gives results ...
We propose the use of Thornton's Separability Index as a simple measure of subset merit which is fast and easy to calculate, but gives results which are ...
Let SIM and SIM,^ be SIM (Separability Index Matrix) of a feature X and SIM of pre- viously selected feature subset V = {x₁,···,x,} in the feature selection ...
[2] Feature Subset Selection using Thornton's separability index and its applicability to a number of sparse proximity-based classifiers. J.Greene 2001 ...
Mar 5, 2013 · Two good methods in unsupervised feature selection are Laplacian Score and SVD-Entropy (For numerical datasets). Cite.
Nov 2, 2024 · The authors used a separability index to measure the goodness of a feature for a class, although the method finally selected the subset of ...
The objective of this study is to determine if the hybrid method present advantages over simple GAs and conventional feature selection algorithms in terms of ...
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