Monte Carlo Tree Search-Based Recursive Algorithm for Feature Selection in High-Dimensional Datasets

Monte Carlo Tree Search-Based Recursive Algorithm for Feature Selection in High-Dimensional Datasets

The complexity and high dimensionality are the inherent concerns of big data. The role of feature selection has gained prime importance to cope with the issue by reducing dimensionality of datasets. The compromise between the maximum classification accuracy and the minimum dimensions is as yet an un...

Полное описание

Библиографические подробности
Главные авторы: Muhammad Umar Chaudhry, Muhammad Yasir, Muhammad Nabeel Asghar, Jee-Hyong Lee
Формат: Статья
Язык:English
Опубликовано: MDPI AG 2020-09-01
Серии:Entropy
Предметы:
feature selection
dimensionality reduction
R-MOTiFS
Monte Carlo Tree Search (MCTS)
heuristic feature selection
Online-ссылка:https://www.mdpi.com/1099-4300/22/10/1093

Internet

https://www.mdpi.com/1099-4300/22/10/1093

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