27 lines
No EOL
831 B
Matlab
27 lines
No EOL
831 B
Matlab
% implements Param_Est, returns the number of eigenvectors needed to
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% explain 90% of the variance in the data, and displays a plot where the
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% x-axis is the number of eigenvectors and the y-axis is the percentage of
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% variance explained.
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function [neigenvectors] = ProportionOfVariance(training_data)
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% stack data
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data = vertcat(training_data);
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% perform PCA
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[~,~,latent] = pca(data);
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% compute proportion of variance explained
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all_eigs = sum(latent);
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prop_var = cumsum(latent) / all_eigs;
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% show figure of proportion of variance explained where the x-axis is the number of eigenvectors and the y-axis is the percentage of
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% variance explained
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subplot(2,1,1);
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plot(find(latent), latent);
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subplot(2,1,2);
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plot(find(prop_var), prop_var);
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neigenvectors = find(prop_var > 0.9, 1);
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end % Function end |