reduce decay factor for sampling weights
@@ -175,7 +175,7 @@ class BlockLearner(Learner):
# the vote it puts on those few pairs will be worth more than
# a predicate that covers almost all the record pairs
proportion = len(covered) / max_cover
- weight: float = numpy.exp(-1000 * proportion)
+ weight: float = numpy.exp(-10 * proportion)
if weight and proportion != 1:
for pair in covered:
weights[pair] = weights.get(pair, 0.0) + weight
