Optimal feature selection through reinforcement learning and fuzzy signature for improving classification accuracy

It is the main objective of feature selection to reduce the computational cost of a predictive model while increasing its performance. For feature selection, an exact search approach is used to evaluate all possible combinations of features in exponential time. The use of meta-heuristic algorithms i...

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Vydáno v:	Multimedia tools and applications Ročník 84; číslo 10; s. 6931 - 6965
Hlavní autoři:	Mansouri, Najme, Zandvakili, Aboozar, Javidi, Mohammad Masoud
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.03.2025 Springer Nature B.V
Témata:	Accuracy Adaptive algorithms Algorithms Classification Computer Communication Networks Computer Science Data Structures and Information Theory Exploitation Feature selection Greedy algorithms Heuristic methods Machine learning Multi-armed bandit problems Multimedia Information Systems Optimization Parameters Prediction models Redundancy Special Purpose and Application-Based Systems Fuzzy signature Feature selection Greedy Multi-Armed Bandit Reinforcement learning Classification
ISSN:	1573-7721, 1380-7501, 1573-7721
On-line přístup:	Získat plný text
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