An Algorithm of Incremental Bayesian Classifier Based on K-Nearest Neighbor

Article Preview

Abstract:

The learning sequence is an important factor of affecting the study effect about incremental Bayesian classifier. Reasonable learning sequence helps to strengthen the knowledge reserve of the classifier. This article proposes an incremental learning algorithm based on the K-Nearest Neighbor. Through calculating k maximum similar distance between test set and training set ,dividing and structuring the sequence of class number and the sequence of sum of class weight. According to the undulation degree of sequence, the instance including stronger class information is chosen to enter the learning process firstly. The experimental result indicates that the algorithm is effective and feasible.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

1455-1459

Citation:

Online since:

November 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] IRINA RISH, JOSEPH L HELLERSTEIN, JAYRAM THATHACHAR. An Analysis of Data Characteristics that Affect Naive Bayes Performance[S]. RC21993, (2001).

Google Scholar

[2] DOMINGOS, PAZZANI M. On the optimality of the simple Bayesian classifier under zero-one loss[J]. Machine Learning, 1997, 29(23): 103-130.

Google Scholar

[3] GONG Xiu-Jun, LIU-Shao-Hui, SHI Zhong-Zhi. An Incremental Bayes Classifical Model[J]. CHINESE JOURNAL OF COMPUTERS, 2002, 25(6): 645-650.

Google Scholar

[4] JIANG Mao-Sheng, WANG Hao, YAO Hong-Liang. Studies on Incremental Learning Sequence Algorithm of Naïve Bayesian Classifier[J]. Computer Engineering and Applications, 2004. 14 : 57-59.

Google Scholar

[5] PAN Li-fang, YANG Bing-ru. Study on KNN arithmetic Based on cluster[J]. Computer Engineering and Design, 2009. 30(18) : 260-262.

Google Scholar

[6] DING Li-hua, ZHANG Xiao-gang. Learning Incremental Bayesian Algorithm Based on Class Support[J]. Computer Engineering, 2008. 34(22) : 218-219.

Google Scholar

[7] XIE Chong-feng; LI Xing. A Sequence-Based Automatic Text Classification Algorithm[J]. Journal of Software, 2002, 13(4): 783-789.

Google Scholar