Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/15018#discussion_r92298473 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala --- @@ -344,27 +344,30 @@ class IsotonicRegression private (private var isotonic: Boolean) extends Seriali } var i = 0 - val len = input.length - while (i < len) { - var j = i - - // Find monotonicity violating sequence, if any. - while (j < len - 1 && input(j)._1 > input(j + 1)._1) { - j = j + 1 - } + val n = input.length - 1 + var notFinished = true + + while (notFinished) { + i = 0 + notFinished = false + + // Iterate through the data, fix any monotonicity violations we find + // We may need to do this multiple times, as pooling can introduce violations + // at locations that were previously fine. + while (i < n) { + var j = i + + // Find next monotonicity violating sequence, if any. + while (j < n && input(j)._1 >= input(j + 1)._1) { + j = j + 1 + } - // If monotonicity was not violated, move to next data point. - if (i == j) { - i = i + 1 - } else { - // Otherwise pool the violating sequence - // and check if pooling caused monotonicity violation in previously processed points. - while (i >= 0 && input(i)._1 > input(i + 1)._1) { + // Pool the violating sequence with the data point preceding it + if (input(i)._1 != input(j)._1) { --- End diff -- I believe the logic is: * If equality holds here, then either (a) i = j or (b) the block [i,j] has equal elements. * A violation could be introduced but will be caught on the next iteration of the outer loop.
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