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Different results when using unsupervised learning and faces dataset

Open karayaneva opened this issue 3 years ago • 1 comments

I am trying to use the unsupervised learning tutorial, which uses the faces dataset from scikit-learn. I have downloaded the files and run them using the Jupyter Notebook. This is the link: https://github.com/amueller/introduction_to_ml_with_python/blob/master/03-unsupervised-learning.ipynb

However, I get different results when I try to visualize the noisy images, please see below:

unsupervised

This is what the expected result should look like:

unsupervised2

I assume that different versions of Python and packages could be the problem. I am using Python 3.10 and the newest versions of all packages. Any suggestions why this is happening will be appreciated.

karayaneva avatar Dec 02 '22 11:12 karayaneva

What are the minimum and maximum values of image for you? On page 151 I'm dividing the entries by 255. Did you do that?

amueller avatar Dec 21 '22 23:12 amueller