(normalize(X) * normalize(X)).sum(axis=1) works fine here.
But I was unaware of these quirks in Python's implementation of pow:
Numpy seems to be consistent in returning nan when a negative float is
raised to a non-integer (or equivalent float) power. By only calculating
integer powers of negativ
Why would the square of a real number ever be negative?
I believe the "quirk" in python is just operator precedence,
as the power gets evaluated before applying the unary "-"
On Sun, Oct 8, 2017 at 11:34 AM Joel Nothman wrote:
> (normalize(X) * normalize(X)).sum(axis=1) works fine here.
>
> But
Ah of course. Thanks.
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Hi,
As Joel said LOF is not designed to be applied on unseen data. Therefore
there is no public predict.
Albert
On Sun 8 Oct 2017 at 06:17, Joel Nothman wrote:
> actually I'm probably wrong there, but you may not be able to use accuracy
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