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https://issues.apache.org/jira/browse/SPARK-21594?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph Wang reopened SPARK-21594:
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> Missing probability output from MutilayerPerceptronClassifier
> -------------------------------------------------------------
>
> Key: SPARK-21594
> URL: https://issues.apache.org/jira/browse/SPARK-21594
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Affects Versions: 2.2.0
> Environment: SPARK, PySpark,Scala, SparkR
> Reporter: Joseph Wang
> Original Estimate: 168h
> Remaining Estimate: 168h
>
> The semi-supervised learning efforts have just started in Spark machine
> learning library.
> This is a very important direction for limited and costly labelled data.
> With the effort, the warm up time for supervised learning can be minimized.
> One of the key feature is to be able to output probability in the existing
> machine learning library for selecting the unlablled data by probability
> including self-training. The algorithm which has a tendency to overfit is
> particularly useful. For example, multilayer perceptron classifier(MLP) is
> one of the case.
> I found this is not possible with MLP(or neural network). This is an
> inconsistent offering which needs to be improved.
> thanks
> Joseph
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