Scipy causes penalty each turn

Scipy causes penalty each turn


Hey C1 Team,

the last days I did some experiments with some “lazy training” approaches. I know that they are time cosuming but I’m pretty sure that they fit some of my ideas. So I started to implement a own function for the euclidean distance.

> # calculate the Euclidean distance between two vectors
> def _euclidean_distance(self, row1, row2):
>         distance = 0.0
>         for i in range(len(row1)-1):
>             distance += (row1[i] - row2[i])**2
>         return sqrt(distance)

this methode takes 4,5 - 5 seconds with my training data. So I started to implement the euclidean with scipy because it is more preformant.

> from scipy.spatial import distance
> distance.euclidean(row1, row2)

this approach takes only 2 seconds.

Now, I uploaded one Algo with Scipy and I got a penalty each turn. I uploaded another algo and used my own implementation of Euclidean and get no penalty.



The penalty comes from to much train data. I reached the computing limit. I reduced the dimenstion and the dataset and the code works with and without scipy. This is no Bug!