Switched to using scikit-learn 0.14's method for handling scoring functions.

The main changes for this pull request are:

-  Can now use any objective function sklearn supports (i.e., any valid argument for `scorer` when instantiating `GridSearchCV`).
-  Removed ml_metrics dependency and we now support custom weights for kappa (through the API only so far)
-  Require's scikit-learn 0.14+
-  `accuracy`, `quadratic_weighted_kappa`, `unweighted_kappa`, `f1_score_micro`, and `f1_score_macro` functions are no longer available under `skll.metrics`. The accuracy and f1 score ones are no longer needed because we just use the built-in ones. As for `quadratic_weighted_kappa` and `unweighted_kappa`, they've been superseded by the `kappa` function that takes a `weights` argument.
-  I also added unit tests (based on Ben Hamner's) for our kappa function.