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. 介绍了感知器算法、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了对比.
Linear classification is a method to classify different kinds of data using linear discriminant function, which is of important significance for Pattern Recognition. Introduced the common linear classification algorithms such as Perceptron Algorithm, Least Error Square Algorithm and Fisher Algorithm. Achieved the data calculation of different algorithm and the 3D visualization of linear classification with scientific computing software Mathematica, and then compared the classification effect of different classification algorithms. (2018-05-13, Mathematica, 1664KB, 下载3次)