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Joseph Wang commented on SPARK-21594: ------------------------------------- The place you suggests seem to be a question asking site. It does not pass this as a ticket to be resolved. I am not sure if it is the right place to go. > 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 -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org