bSSA: Binary Salp Swarm Algorithm With Hybrid Data Transformation for Feature Selection

Feature selection is a technique commonly used in Data Mining and Machine Learning. Traditional feature selection methods, when applied to large datasets, generate a large number of feature subsets. Selecting optimal features within this high dimensional data space is time-consuming and negatively a...

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Vydáno v:	IEEE access Ročník 9; s. 14867 - 14882
Hlavní autoři:	Shekhawat, Sayar Singh, Sharma, Harish, Kumar, Sandeep, Nayyar, Anand, Qureshi, Basit
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Algorithms Computer science Data mining Data transformation Datasets fast independent component analysis Feature extraction Feature selection Genetic algorithms Independent component analysis Machine learning Optimization Principal component analysis Principal components analysis salp swarm optimizer Search algorithms Support vector machines Transforms
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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