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.

Greetings!