PCA Classify Example Script - Revision history

Mjeppesen at 06:27, 20 January 2022

2022-01-20T06:27:07Z

← Older revision		Revision as of 06:27, 20 January 2022
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	S = boxplot(X_g2new');		S = boxplot(X_g2new');

	~~[[category:Protocols]]~~
	[[category:Data_Processing_and_Analysis]]		[[category:Data_Processing_and_Analysis]]
			[[category:Needs_Updating]]<!--This is mostly psuedocode need to clarify to script status-->

Mjeppesen: Added to Category

2021-09-11T04:46:29Z

Added to Category

← Older revision		Revision as of 04:46, 11 September 2021
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	S = boxplot(X_g2new');		S = boxplot(X_g2new');

	[[category:~~Protocols\|~~Protocols]]		[[category:Protocols]]
	[[category:Data_Processing_and_Analysis]]		[[category:Data_Processing_and_Analysis]]

Mjeppesen: Added to Category

2021-09-11T03:26:29Z

Added to Category

← Older revision		Revision as of 03:26, 11 September 2021
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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]]

Acrook: 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..."

2021-01-07T17:13:17Z

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..."

New page

== 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');