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.