bayes for days

feat(training): --self-play, so the label has something to vary master

Against Princess the bot loses every game, so every label is the same number and least squares has nothing to separate. More losses do not help: the problem is the variance, not the count. Seating the bot on both sides gives an even split by construction. The cost is the one plan/training.md names, so weights fitted this way are a starting point to re-measure against Princess, never a reported number.


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