Comments (1)
As discussed offline, the problem wasn't in the random_state but in the dataset. The dataset was:
0 1
0.5 1
1 1
Since the second column was all 1s, it got normalized as all 0's, ending with a small dataset where all the rows where linearly dependent, which then caused problems when extracting the 2 eigenvectors required by PCA (with rank = 2), and made the eigenvectors to have NaN values.
Although the problem is in the dataset, the exception that is thrown is not clear to read, so changing the exception message makes sense.
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