Support HyperParameter composition

Some classifiers accept multiple types for the same HyperParameter.
An example of this is the max_features hyperparameter of the RandomForestRegressor:

max_features : int, float, string or None, optional (default="auto")
The number of features to consider when looking for the best split:

• If int, then consider max_features features at each split.
• If float, then max_features is a percentage and
  int(max_features * n_features) features are considered at each split.
• If "auto", then max_features=n_features.
• If "sqrt", then max_features=sqrt(n_features).
• If "log2", then max_features=log2(n_features).
• If None, then max_features=n_features.

Combining multiple HyperParameters, or multiple Ranges of the same type, in a single HyperParameter (e.g. STRING + INT + FLOAT) should be possible in order to cover cases like this one.