Computer Science ›› 2015, Vol. 42 ›› Issue (4): 199-205.doi: 10.11896/j.issn.1002-137X.2015.04.040

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Statistical Testing Based Research on Kernel Evaluation Measures

WANG Pei-yan and CAI Dong-feng   

  • Online:2018-11-14 Published:2018-11-14

Abstract: This paper explored the research on evaluating kernel function by using statistical testing.By employing kernel,normalized kernel,centered kernel and kernel distance as geometric measure among samples in feature space,and applying 7 statistical testing methods such as t-test and f-test,this paper evaluated the distributional difference between the geometric measures among samples from same classes and the geometric measure among samples from different classes.The experimental results of kernel selection on 11 UCI datasets show that the kernel evaluation measures based on statistical testing reach or exceed the performance of KTA and FSM,etc.And we found that the two types of data distribution differences are mainly reflected in the variance difference.Moreover,the formatting of kernel function such as normalization or centering can change the feature space,and make the evaluation distorted.

Key words: Kernel function,Kernel evaluation,Statistical testing

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