I see, as far as I know, your X input array should be a n_samples x n_features
array. Is this true in your case?
Btw. instead of converting the inputs to Python lists , you could also get the
counts via
a1 = x[x == 1.0].shape[0]
b1 = y[y == 1.0].shape[0]
And maybe a few extra lines
assert set(np.unique(x)).issubset({0.0, 1.0})
assert set(np.unique(x)).issubset({0.0, 1.0})
would be useful for debugging purposes?!
> On Jan 12, 2016, at 2:01 PM, Herbert Schulz <[email protected]> wrote:
>
> Yes, it is a number between 0 and 1.
>
> but im calculating it, depended on 2 samples. So x and y. And if im counting
> the 1's in x and the 1's in y, i should get the coef with return float(c)/(a1
> + b1 - c)
>
> But i cannot count 1's in x if x is a skalar.
>
>
>
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