- Use the 'pca()' function in MATLAB to perform PCA on your dataset and then determine the number of principal components you want to use for the reconstruction.
- Determine the number of principal components you want to use for the reconstruction.
- If your data was originally in a matrix or image format, reshape the reconstructed data back into the original shape and then use the 'imagesc()' function in MATLAB to plot the reconstructed heatmap image.
How to plot a heatmap image using PCA loadings?
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I need some guidance to plot or reconstruct a heatmap image as the attached image used PCA loading.
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Answers (1)
Vandit
on 30 Aug 2023
Hi,
To plot or reconstruct a HeatMap image using PCA loadings, you can follow these general steps:
Here's an example code snippet that demonstrates these steps:
%Note:You should replace data with your actual data matrix or image. Adjust the numComponents variable to select the desired number of principal components for reconstruction
% Perform PCA on your data
pcaObj = pca(data);
% Select the desired number of principal components
numComponents = 10;
selectedComponents = pcaObj.coeff(:, 1:numComponents);
% Compute the scores for the selected principal components
scores = data * selectedComponents;
% Reconstruct the data
reconstructedData = scores * selectedComponents';
% Reshape the reconstructed data
reconstructedData = reshape(reconstructedData', size(data, 2), size(data, 1));
% Plot the heatmap
figure;
imagesc(reconstructedData);
colorbar;
To know more about 'pca' and 'imagesc' function, refer to the link below:
Hope this helps.
Thankyou
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