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Spark implementation of Fayyad's discretizer based on Minimum Description Length Principle (MDLP)

Results 7 spark-MDLP-discretization issues
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Bumps [junit](https://github.com/junit-team/junit4) from 4.12 to 4.13.1. Release notes Sourced from junit's releases. JUnit 4.13.1 Please refer to the release notes for details. JUnit 4.13 Please refer to the release notes...

dependencies

https://github.com/sramirez/spark-MDLP-discretization/issues/36 Fix to load method for Spark 2.x.x. Since Spark 1.6 is old now, this fix is valid. Has been tested and is working fine.

I would like to discretize the Epsilon dataset that it has 2k features and 400k records. To achieve this, I utilized the Spark 2.3.0. Once I execute the code, I...

I would like to investigate creating a PR to add a jenkins file to allow for automated building if there is a jenkins server. The jenkins file will have no...

Steps to reproduce with [this dataset](https://github.com/MarcKaminski/stackoverflow/blob/master/datasets/cars.data) `spark-shell --jars "/path/to/spark-MDLP-discretization-1.3.jar"` ```scala import org.apache.spark.ml.{Pipeline, PipelineModel} import org.apache.spark.ml.feature._ val carsPath = "/path/to/cars.data" val mdlPath = "/path/to/save/mdl" val df = spark.read.option("header", true) .option("inferSchema", true)...

This is a strange one, and not that easy to reproduce. If I run the tests a bunch of times, I have noticed that on occasion, I get an extra...