The Optimization of Threshold-Based Naive Bayesian Algorithm

被引：0

作者：

Wang Xin ^{[1
]}

Jiang Hua ^{[1
]}

机构：

[1] Guilin Univ Elect Technol, Sch Comp Sci & Control, Guilin 541004, Peoples R China

来源：

THIRD INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING | 2009年

关键词：

Naive Bayesian classification; text classification; information filtering; overflow;

D O I：

10.1109/WGEC.2009.161

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In order to realize the text classification and spam filtering, the Naive Bayesian algorithm estimate what class are the text in by basing on some statistical probability values in accordance with the characteristic in straining sample, but it is easy to expose the overflow problem, this article will optimize the algorithm by setting the threshold, the optimization strategy is comparing the times that the probability of each class exceed the threshold and the accumulated probability values at the same times. Compare with the existing method, experimental result show the new method not only can solve the overflow problem, but also improve the classification effect effectively.

引用

页码：762 / 764

页数：3