Multilabel Feature Selection Using Mutual Information and ML-ReliefF for Multilabel Classification

Multilabel Feature Selection Using Mutual Information and ML-ReliefF for Multilabel Classification

Recently, multilabel classification algorithms play an increasingly significant role in data mining and machine learning. However, some existing mutual information-based algorithms ignore the influence of the proportions of labels on the correlation degree between features and label sets. Besides, t...

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Bibliographic Details
Main Authors: Enhui Shi, Lin Sun, Jiucheng Xu, Shiguang Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Feature selection
mutual information
ReliefF
multilabel classification
Online Access:https://ieeexplore.ieee.org/document/9162124/

Internet

https://ieeexplore.ieee.org/document/9162124/

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