Thank you. It seems that information value can only be calculated for a
binary classification dataset, however my response variable is continuous.
On 20/04/17 05:51, urvesh patel wrote:
I believe your random variable by chance have some predictive power. In
R, use Information package and chec
I'm not totally sure of what you're trying to do, but here are some
remarks that may help you:
1. in modelfit = model.fit(count_vect, enc), the enc parameter is not
used, only the count_vect matrix is used
2. when you use kneighbors you get vectors corresponding to wiki['text']
not to wiki['name']
The problem is the misuse of the label encoder. See
https://github.com/scikit-learn/scikit-learn/issues/8767
On 20 April 2017 at 19:58, Alex Garel wrote:
> I'm not totally sure of what you're trying to do, but here are some
> remarks that may help you:
>
> 1. in modelfit = model.fit(count_vect,
