[GitHub] spark issue #19106: [SPARK-21770][ML] ProbabilisticClassificationModel fix c...

2017-10-10 Thread srowen
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2017-10-09 Thread WeichenXu123
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2017-09-20 Thread WeichenXu123
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2017-09-19 Thread SparkQA
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2017-09-19 Thread SparkQA
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2017-09-18 Thread jkbradley
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/19106 These are fair arguments. I guess it makes sense to throw an exception; that's fine with me. --- - To unsubscribe, e-mail:

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2017-09-13 Thread SparkQA
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2017-09-12 Thread srowen
Github user srowen commented on the issue: https://github.com/apache/spark/pull/19106 That's my sentiment too, that it is likely patching over another problem. I'd go with Joseph on this, but at least, issue a warning maybe? I also would support throwing an exception to fail

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2017-09-12 Thread sethah
Github user sethah commented on the issue: https://github.com/apache/spark/pull/19106 Ok, I guess I'm surprised that someone even noticed this... So, basically, we are changing the behavior of a private function for a specific case which is actually impossible to ever run

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2017-09-12 Thread smurching
Github user smurching commented on the issue: https://github.com/apache/spark/pull/19106 @sethah I haven't heard of anybody hitting this issue in practice, but it did seem best to ensure that valid probability distributions would be produced regardless of input. There was some

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2017-09-11 Thread sethah
Github user sethah commented on the issue: https://github.com/apache/spark/pull/19106 I'm confused how this issue was discovered in the first place. Did someone actually train an RF/DT and receive all zero probabilities? If so, shouldn't there be a unit test that recreates that

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2017-09-11 Thread smurching
Github user smurching commented on the issue: https://github.com/apache/spark/pull/19106 This looks good to me! @srowen would you be able to give it another look? --- - To unsubscribe, e-mail:

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