[svlpbpqc] Machine learning chess heuristic

A computer program plays a better opponent, losing.  Look back on the program's analysis, particularly to each move's principal variation.  Where did something go wrong?  Usually when the opponent ultimately plays a much better move than the move predicted as the PV.

Was the failure because of a bad board evaluation?  Because a node was pruned that shouldn't have been?  For these cases, we may be able to apply a machine learning classification algorithm, to derive a new heuristic which puts the move on the correct side of the classifier.

If the failure was purely due to the horizon effect, for example the program playing a deeper version of itself, this will not (or at least should not) be too effective (though temporal difference learning has had its success).

Surely this has been done.