Entropy based fuzzy least squares twin support vector machine for class imbalance learning

Deepak Gupta; Bharat Richhariya

doi:10.1007/s10489-018-1204-4

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Entropy based fuzzy least squares twin support vector machine for class imbalance learning

Deepak Gupta Bharat Richhariya

Year: 2018 Journal: Applied Intelligence Vol: 48 (11)Pages: 4212-4231 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-018-1204-4

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Keywords:

Support vector machine Artificial intelligence Computer science Fuzzy logic Machine learning Structured support vector machine Entropy (arrow of time) Algorithm Defuzzification Pattern recognition (psychology) Data mining Mathematics Fuzzy number Fuzzy set

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Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Entropy based fuzzy least squares twin support vector machine for class imbalance learning

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