Github user chouqin commented on the pull request:
https://github.com/apache/spark/pull/2780#issuecomment-58865951
@jkbradley, RandomForestSuite fails because original splits are better fit
for the training data(for example, 899.5 is a split threshold, which is close
to 900.) I think this PR's method to choose splits is more reasonable than the
original method in that the first threshold found by the original method will
be the average value of the first two `featureSamples`.
For example, if `featureSamples` is `Array(0, 1, 2, 3, 4, 5)`, find a split
point using the original method will return 0.5, while this PR's method will
return 2.
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