Du, Zhi-GangPan, Tien-SzuPan, Jeng-ShyangChu, Shu-ChuanQUasi-Affine TRansformation Evolutionary Algorithm (QUATRE) is a currently emerging meta-heuristic evolutionary algorithm. QUATRE has the ability to balance exploitation and exploration in the optimization process, and the algorithm optimization uses matrix operations to greatly reduce the time complexity for solving the same problem. This series of advantages makes this algorithm adopted by a large number of researchers. In this paper, QUATRE is used to optimize the Feature Selection (FS) of the wrapper method. K-Fold Cross-Validation (KFCV) method is also used to divide the test set and training set of the sample, and then use the K Nearest Neighbor (KNN) algorithm for feature classification. In the optimization process, we use a threshold (choice) for feature identification to select useful features. Finally, the 9 standard test data sets in UCI are used to verify the effectiveness of the QUATRE algorithm.


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    Title :

    QUasi-Affine TRansformation Evolutionary Algorithm for Feature Selection


    Additional title:

    Smart Innovation, Systems and Technologies


    Contributors:


    Publication date :

    2021-11-30


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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