[BUG] Cluster predict proba edge cases

[chrisholder]

Reference Issues/PRs

What does this implement/fix? Explain your changes.

There were two edge cases with the clustering predict_proba function that would cause crashes.

1. If there wasn't at least 1 prediction in every cluster
2. If the prediction didn't use cluster values of 0-n_clusters. For example I used a k-medoids package that when predict was called returned [22, 22, 32, 3, 32, 22] where instead of the cluster values being a value from 0-n_clusters it was referring to the index of the cluster centre that each value was assigned to.

This PR makes two main changes to address the above.

1. Instead of using .shape[0] to create the dist array n_clusters is used (when available isn't required):

            n_clusters = self.n_clusters
            if n_clusters is None:
                n_clusters = int(max(preds)) + 1
            dists = np.zeros((X.shape[0], n_clusters))

2. A additional sanitisation of the predict result is done to convert predictions value to 0-n_clusters. This allows the other logic to work if the predictions doesn't return 0-n_clusters:

  unique = np.unique(preds)
  for i, u in enumerate(unique):
      preds[preds == u] = i

Does your contribution introduce a new dependency? If yes, which one?

Any other comments?

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[TonyBagnall]

is this related to #882?

[chrisholder]

No this is just a general bug fix