v0.3.3: better pipeline support and thread safety

Version 0.3.3:

Highlights:

• Adding support for cross validated metrics
• Better support for pipelines by using kernel explainer
• Making explainer threadsafe by adding locks
• Remove outliers from shap dependence plots

Breaking Changes

• parameter permutation_cv has been deprecated and replaced by parameter cv which
  now also works to calculate cross-validated metrics besides cross-validated
  permutation importances.

New Features

• metrics now get calculated with cross validation over X when you pass the
  cv parameter to the explainer, this is useful when for some reason you
  want to pass the training set to the explainer.
• adds winsorization to shap dependence and shap interaction plots
• If shap='guess' fails (unable to guess the right type of shap explainer),
  then default to the model agnostic shap='kernel'.
• Better support for sklearn Pipelines: if not able to extract transformer+model,
  then default to shap.KernelExplainer to explain the entire pipeline
• you can now remove outliers from shap dependence/interaction plots with
  remove_outliers=True: filters all outliers beyond 1.5*IQR

Bug Fixes

• Sets proper threading.Locks before making calls to shap explainer to prevent race
  conditions with dashboards calling for shap values in multiple threads.
  (shap is unfortunately not threadsafe)

Improvements

• single shap row KernelExplainer calculations now go without tqdm progress bar
• added cutoff tpr anf fpr to roc auc plot
• added cutoff precision and recall to pr auc plot
• put a loading spinner on shap contrib table