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Weighted Gini index feature selection method for imbalanced data
Haoyue Liu
,
Mengchu Zhou
, Xiaoyu Sean Lu
, Cynthia Yao
Electrical and Computer Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
50
Scopus citations
Overview
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Dive into the research topics of 'Weighted Gini index feature selection method for imbalanced data'. Together they form a unique fingerprint.
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Keyphrases
Gini Coefficient
100%
Feature Selection Methods
100%
Imbalanced Data
100%
Feature Selection
75%
F-measure
75%
ROC-AUC
75%
F-statistics
50%
AUC Measure
50%
High Performance
25%
Cancer Diagnosis
25%
Real-world Application
25%
Fraud Detection
25%
Minority Class
25%
Chi-square
25%
Selected Features
25%
Class Imbalance Problem
25%
Text Classification
25%
Classification Diagnosis
25%
Majority Problem
25%
Imbalanced Distribution
25%
XGBoost
25%
Statistical Index
25%
Computer Science
Feature Selection
100%
Imbalanced Data
100%
Good Performance
28%
Experimental Result
14%
Fraud Detection
14%
World Application
14%
Comparison Result
14%
Data Distribution
14%
Minority Class
14%
Average Result
14%
Text Classification
14%
Extreme Gradient Boosting
14%