逐步判别分析的主函数

用于分类

[sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10)

输入变量

x为训练集.每行为一个样本，每列为一个变量.

Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9]

Test为待分类样本.

输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率.

author 王新 2012.4.8

例子Sample:

load fisheriris

x=meas

Class_x=[50,50,50]

Test=meas(1:5,:)

Fa1=4

[sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)-　Stepwise discriminant analysis for the classification of the main function　 [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10)　 input variables　 x as the training set, each conduct a sample of each as a variable.　Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9]　Test sample to be classified.　output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability.　author Wang 2012.4.8　examples Sample:　load fisheriris　x = meas　 Class_x = [50,50,50]　 Test = meas (1:5, :)　 Fa1 = 4　 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1)