PCA Classify Example Script: Difference between revisions
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(Created page with "== PCA Classify Function == Project new samples into PCA model using appropriate scaling. Xtest = test/second dataset;clsRtest = test/second class. result = PCA mode...") |
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scores = T_g2new; | scores = T_g2new; | ||
S = boxplot(X_g2new'); | S = boxplot(X_g2new'); | ||
[[category:Protocols|Protocols]] | |||
[[category:Data_Processing_and_Analysis]] |
Revision as of 03:26, 11 September 2021
PCA Classify Function
Project new samples into PCA model using appropriate scaling.
Xtest = test/second dataset;clsRtest = test/second class. result = PCA model (MVApack) mn = result.mean.X;sd = result.scale.X; X_g1a = Xtest;%X_g2a = Xtrain; X_g2new = (X_g1a-(repmat(mn,[size(X_g1a,1),1])))./(repmat(sd,[size(X_g1a,1),1]));%size(X_g2new) T_g2new = X_g2new*result.P; scores = T_g2new; S = boxplot(X_g2new');