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[Matlab]
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- Update:
- 2013-06-17
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- 王新
Description: Stepwise discriminant analysis for the classification of the main function [sel, c 0, 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)
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StepclaassV2.m
adddataV2.m
calU.m
chg.m
deldataV2.m
meas.mat
Stepclaass.m
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