How do I use PCA

3 Ansichten (letzte 30 Tage)
kash
kash am 17 Dez. 2011
Beantwortet: Gautam am 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

Antworten (1)

Gautam
Gautam am 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

Kategorien

Mehr zu Dimensionality Reduction and Feature Extraction finden Sie in Help Center und File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by