How do I use PCA

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kash
kash on 17 Dec 2011
Answered: Gautam on 2 Jan 2025
I have extracted features of an image,and stored in an folder,now i want to select best features from it using PCA AND have to comapre these features ,with the features of query image and retrieve it,please help

Answers (1)

Gautam
Gautam on 2 Jan 2025
Hello kash,
To perform feature selection using PCA, you can follow the MATLAB code below:
% Center the data
meanFeatures = mean(Features);
centeredFeatures = allFeatures - meanFeatures;
% Perform PCA
[coeff, score, ~, ~, explained] = pca(centeredFeatures);
% Select the number of principal components to retain (e.g., 95% variance)
cumulativeVariance = cumsum(explained);
numComponents = find(cumulativeVariance >= 95, 1);
% Reduce dimensionality
reducedFeatures = score(:, 1:numComponents);
You can further use Euclidean distance to compare the query features with the stored features, and identify the closest matches

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