*Bounty: 50*

*Bounty: 50*

After running xgboost model with:

```
objective = 'binary:logistic'
eval_metric = 'logloss'
```

I have a group of 3 variables that have the highest values of gain. Now, if I replace each one of the 20 more important variables according to this metric by their mean one by one and calculate the kolmogorov smirnov coefficient (KS), I get that the one that reduces the most the ks is not one of those 3, but one that has a relative low gain.

Gain

```
Gain Cover
v1 21.5% 2.5%
v2 12.9% 4.1%
v3 11.1% 1.8%
v4 3.5% 3.4%
v5 2.7% 1.7%
v6 2.4% 2.5%
v7 2.3% 2.2%
v8 2.2% 1.9%
v9 1.9% 4.0%
v10 1.9% 2.0%
v11 1.9% 0.9%
v12 1.6% 4.6% *****
```

ks of replacing each variable by its mean (one by one)

```
v12 39% *****
the rest 45%
```

How is this explained? Thanks.