NDLI: A comparative study among different kernel functions in flexible naïve Bayesian classification

Content Provider	IEEE Xplore Digital Library
Author	Liu, J.N.K. Yu-Lin He Xi-Zhao Wang Yan-Xing Hu
Copyright Year	2011
Description	Author affiliation: Machine Learning Center, Faculty of Mathematics and Computer Science, Hebei University, Baoding 071002, China (Yu-Lin He; Xi-Zhao Wang) \|\| Department of computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (Liu, J.N.K.; Yan-Xing Hu)
Abstract	When determining the class of the unknown example by using naïve Bayesian classifier, we need to estimate the class conditional probabilities for the continuous attributes. In flexible Bayesian classifier, the Gaussian kernel function is frequently used for classification task under the framework of Parzen window method. In this paper, the other six kernel functions (uniform, triangular, epanechnikov, biweight, triweight and cosine) are introduced in the flexible naïve Bayesian. The performances of these seven kernels are compared in 30 UCI datasets. The experimental comparisons are carried out according to the following three aspects: the classification accuracy, ranking performance and the class probability estimation. The latter two are measured by the area under the ROC curve (AUC) and the conditional log likelihood (CLL). The related kernels are compared via two-tailed t-test with a 95 percent confidence level and the Friedman's test using the 0.05 critical level. The experimental results show that the most commonly used Gaussian kernel can not achieve the best classification accuracy and AUC. However, on the CLL, the Gaussian kernel is statistically significantly better than the other six kernels. Finally, the corresponding analyses are given based on the experimental results.
Starting Page	638
Ending Page	643
File Size	225455
Page Count	6
File Format	PDF
ISBN	9781457703058
ISSN	21601348
e-ISBN	9781457703089
DOI	10.1109/ICMLC.2011.6016813
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Accuracy Bayesian methods Breast cancer Machine learning Estimation Heart CLL Naïve Bayesian classifier density estimation Gaussian uniform triangular epanechnikov biweight triweight cosine AUC
Content Type	Text
Resource Type	Article

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