Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/8314#issuecomment-152989755
The last failure is in `MultilayerPerceptronClassifierSuite`. The test is
backwards in that expected/actual are flipped. It should be
assert(lrMetrics.confusionMatrix ~== mlpMetrics.confusionMatrix absTol
100)
That is the output ought to look something like
```
[info] 152.0 74.0 121.0
[info] 65.0 167.0 64.0
[info] 114.0 76.0 167.0
```
... which is a little strange since this shows a fairly poor classifier's
confusion matrix.
There are 2 seeds in this test and setting them to a range of values
succeeds in every case for me. This one might be a matter of picking a
different seed? although it is a little funny that in this case the MLP
classifier never predicted class 0. But that's a different issue.
I also note that LogisticRegressionSuite uses a regular java.util.Random
instead of XORShiftRandom. Might be worth adjusting, unless it causes more
failures.
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