常用线性分类器算法及基于Mathematica三维可视化  

Commonly Used Linear Classification Algorithms and 3D Visualization Based on Mathematica

作　　者：朱静雯[1] 向仕兵 

机构地区：[1]西南科技大学理学院,绵阳621010

出　　处：《现代计算机》2017年第7期14-19,共6页Modern Computer

摘　　要：线性分类是利用线性判别函数将不同类数据进行分类的方法,在模式识别中有着重要应用。介绍感知器算法、最小误差平方算法、Fisher算法及支持向量机学习算法等常用线性分类算法。利用Mathematica编程实现计算及可视化三维线性分类,并对不同分类算法的分类效果进行对比。Linear classification is a method to classify different kinds of data using linear discriminant function, which is of important significance for Pattern Recognition. Introduces the common linear classification algorithms such as Perceptron Algorithm, Least Error Square Algorithm and Fisher Algorithm. Achieves the data calculation of different algorithm and the 3D visualization of linear classification with scientific computing software Mathematica, and then compares the classification effect of different classification algorithms.

关 键 词：线性分类器 分类算法 MATHEMATICA 三维可视化 效果对比 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]