unexplained contribution can be larger than 1

[rmohan91]

Eg. In the output, the unexplained contribution weights sometimes go over 100 (see image).

[Dark3clipse]

The unexplained contribution is simply the difference between the sum of the feature contributions and the prediction. While the prediction is contained within the percentage limits [-1, 1], the feature contributions are not. Hence, the difference is not either. Therefore it can occur that the unexplained contribution is over 100%.

That said, an absolute contribution that is larger than 1 indicates the underlying predictor is performing very badly and it is not clear if the current explanations are helpful to users to understand that the model is performing poorly.

[Dark3clipse]

Changed the label of this issue from bug to enhancement, where it may be useful in the future to create more clear explanations in the case of unexplained contributions > 1.