Feature Selection for High Dimensional Data Using Weighted K-Nearest Neighbors and Genetic Algorithm

Feature Selection for High Dimensional Data Using Weighted K-Nearest Neighbors and Genetic Algorithm

Too many input features in applications may lead to over-fitting and reduce the performance of the learning algorithm. Moreover, in most cases, each feature containing different information content has different effects on the prediction target. Therefore, a feature selection method for calculating...

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Bibliographic Details
Main Authors: Shuangjie Li, Kaixiang Zhang, Qianru Chen, Shuqin Wang, Shaoqiang Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Feature selection
weighted K-nearest neighbors
genetic algorithm
real coding
Online Access:https://ieeexplore.ieee.org/document/9151875/

Internet

https://ieeexplore.ieee.org/document/9151875/

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