In the first week’s lab on anomaly detection (exercise 2), I have tried both loop and vectorised implementation to find the most appropriate epsilon. I keep getting an assertion error even if I simply copy paste the code from hints:
Wrong best_epsilon. Expected: 0.04 got: 0.28971
Any chance the assertion could be wrong?
Hi!
Can you send me your code so I can take a look?
I have completed the code with loop implementation. Can you provide some hint to do a vectorised implementation.
np.sum(np.logical_and(pred_labels == 1, true_labels == 1)) - is this a correct vectorised implementation?
You do not need to use np.logical_and(). The regular Python logical operator ‘&’ is sufficient.
However I don’t know of any reason why np.logical_and() would not work. I’ve never tried that way.
Please do not post your code on the forum. That is not allowed by the Code of Conduct.
Perhaps the error is in some other cell.
