Issue #563: Use weights in Permutation Feature Importance calculation

[danielarifmurphy]

Issue #563

In this PR:

• Use weights in loss_after_permutation()
• Handle loss functions both with and without sample_weight parameter to maintain backwards compatibility with existing loss functions

Notes:

• One approach would have been to extend all existing loss functions to be compatible with weights, but we thought the calculate_loss() to handle both cases to be more appropriate since this way we can handle any user-defined custom loss function that does not take weights
• The explicit check for the parameter named sample_weight is in line with the scikit-learn signature - any custom loss functions wanting to use weights need to have the parameter named this way too

[hbaniecki]

Thanks!