PROPOSING A NOVEL FEATURE SELECTION ALGORITHM BASED ON HESITANT FUZZY SETS AND CORRELATION CONCEPTS

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Ebrahimpour Mohammad Kazem; EFTEKHARI MAHDI

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Seminar Paper

Paper Information

Seminar: INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND SIGNAL PROCESSING (AISP)
Year:2015 | Issue:1

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Title

PROPOSING A NOVEL FEATURE SELECTION ALGORITHM BASED ON HESITANT FUZZY SETS AND CORRELATION CONCEPTS

Author(s)

Ebrahimpour Mohammad Kazem | EFTEKHARI MAHDI | Issue Writer Certificate

Keywords

FEATURE SELECTION

HESITANT FUZZY SETS

HESITANT CORRELATION

HESITANT CLUSTERING

CORRELATION BASED FEATURE SELECTION

Abstract

IN THIS PAPER, A FEATURE SELECTION (FS) METHOD BASED ON HESITANT FUZZY SETS (HFS) IS PROPOSED. THE RANKING VALUE OF THREE FILTER METHODS (I.E. FISHER, RELIEF, INFORMATION GAIN) FOR EACH FEATURE ARE CONSIDERED AS HESITANT FUZZY ELEMENTS (HFE) OF THAT FEATURE WITH RESPECT TO CLASS RELEVANCY, THEN HESITANT CORRELATION MATRIX OF FEATURES IS CALCULATED. AFTER THAT THREE SIMILARITY MEASURES ARE CONSIDERED TO EVALUATE THE SECOND HESITANT CORRELATION MATRIX OF FEATURES. THE FIRST CORRELATION MATRIX REPRESENTS THE CORRELATION OF FEATURES WITH RESPECT TO THEIR RELEVANCY TO THE CLASS. THE SECOND CORRELATION MATRIX PRESENTS THE CORRELATION BASED ON REDUNDANCY OF FEATURES AMONG THEMSELVES. ONE HESITANT FUZZY SETS CLUSTERING ALGORITHM (HFSCA) IS RUN ON THESE MATRIXES. FINALLY THE INTERSECTION OF CLUSTERS IS CONSIDERD AS A FEATURES SUBSET WHICH CONTAINS THE HIGHLY RELEVANCE AND LOWLY REDUNDANT FEATURES. THE EXPERIMENTAL RESULTS CONFIRM THE ABILITY OF OUR PROPOSED METHOD IN BOTH NUMBER OF SELECTED FEATURES AND ACCURACY COMPARING TO THE OTHER ONES. ...

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APA: Copy

Ebrahimpour, Mohammad Kazem, & EFTEKHARI, MAHDI. (2015). PROPOSING A NOVEL FEATURE SELECTION ALGORITHM BASED ON HESITANT FUZZY SETS AND CORRELATION CONCEPTS. INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND SIGNAL PROCESSING (AISP). SID. https://sid.ir/paper/927465/en

Vancouver: Copy

Ebrahimpour Mohammad Kazem, EFTEKHARI MAHDI. PROPOSING A NOVEL FEATURE SELECTION ALGORITHM BASED ON HESITANT FUZZY SETS AND CORRELATION CONCEPTS. 2015. Available from: https://sid.ir/paper/927465/en

IEEE: Copy

Mohammad Kazem Ebrahimpour, and MAHDI EFTEKHARI, “PROPOSING A NOVEL FEATURE SELECTION ALGORITHM BASED ON HESITANT FUZZY SETS AND CORRELATION CONCEPTS,” presented at the INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND SIGNAL PROCESSING (AISP). 2015, [Online]. Available: https://sid.ir/paper/927465/en

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