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Hi ! Could you help me to due with the question? I don't know how I need to write the code for this question. Thanks
Hi Could you help me to due with the question? I don't know how I need to write the code for this question. Thanks a lot~
Dimensionality Reduction with SVD
for dimensionality reduction, as we have seen earlier. More technically speaking, it corresponds to the number of concepts or dimensions we will extract from the matrix.
Select an appropriate number of singular values to retain based on your chosen criterion if the selected picture is attached in the picture
Print the values in U and Vt Its evident that the last few columns of matrix U contains values so small that their contribution to the data will be minimal.
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