[SPARK-3934] [SPARK-3918] [mllib]  Bug fixes for RandomForest, DecisionTree

SPARK-3934: When run with a mix of unordered categorical and continuous features, on multiclass classification, RandomForest fails. The bug is in the sanity checks in getFeatureOffset and getLeftRightFeatureOffsets, which use the wrong indices for checking whether features are unordered.
Fix: Remove the sanity checks since they are not really needed, and since they would require DTStatsAggregator to keep track of an extra set of indices (for the feature subset).

Added test to RandomForestSuite which failed with old version but now works.

SPARK-3918: Added baggedInput.unpersist at end of training.

Also:
* I removed DTStatsAggregator.isUnordered since it is no longer used.
* DecisionTreeMetadata: Added logWarning when maxBins is automatically reduced.
* Updated DecisionTreeRunner to explicitly fix the test data to have the same number of features as the training data.  This is a temporary fix which should eventually be replaced by pre-indexing both datasets.
* RandomForestModel: Updated toString to print total number of nodes in forest.
* Changed Predict class to be public DeveloperApi.  This was necessary to allow users to create their own trees by hand (for testing).

CC: @mengxr  @manishamde @chouqin @codedeft  Just notifying you of these small bug fixes.
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