NoiseFramework (homepage)

Noise Framework for removing noisy instances with three algorithms: HME-BD, HTE-BD and ENN.

@djgarcia / (2)

In this framework, two Big Data preprocessing approaches to remove noisy examples are proposed: an homogeneous ensemble (HME_BD) and an heterogeneous ensemble (HTE_BD) filter. A simple filtering approach based on similarities between instances (ENN_BD) is also implemented.

Tags

  • 1|machine learning
  • 1|ensemble
  • 1|noise
  • 1|bigdata

How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages djgarcia:NoiseFramework:1.2

sbt

If you use the sbt-spark-package plugin, in your sbt build file, add:

spDependencies += "djgarcia/NoiseFramework:1.2"

Otherwise,

resolvers += "Spark Packages Repo" at "https://repos.spark-packages.org/"

libraryDependencies += "djgarcia" % "NoiseFramework" % "1.2"

Maven

In your pom.xml, add: 
<dependencies>
  <!-- list of dependencies -->
  <dependency>
    <groupId>djgarcia</groupId>
    <artifactId>NoiseFramework</artifactId>
    <version>1.2</version>
  </dependency>
</dependencies>
<repositories>
  <!-- list of other repositories -->
  <repository>
    <id>SparkPackagesRepo</id>
    <url>https://repos.spark-packages.org/</url>
  </repository>
</repositories>

Releases

Version: 1.2 ( 806be2 | zip | jar ) / Date: 2018-04-18 / License: Apache-2.0 / Scala version: 2.11

Version: 1.1 ( 02851b | zip | jar ) / Date: 2017-09-28 / License: Apache-2.0 / Scala version: 2.10

Version: 1.0 ( 699ae0 | zip | jar ) / Date: 2017-03-28 / License: Apache-2.0 / Scala version: 2.10