SpectralLDA-TensorSpark (homepage)

Quick summary: This code implements a spectral (third order tensor decomposition) learning method for learning LDA topic model on Spark.

@FurongHuang / (1)

This package can be used for learning topic models and any other exchangeable latent variable models.

Tags

  • 1|machine learning

How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages FurongHuang:SpectralLDA-TensorSpark:1.0

sbt

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

spDependencies += "FurongHuang/SpectralLDA-TensorSpark:1.0"

Otherwise,

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

libraryDependencies += "FurongHuang" % "SpectralLDA-TensorSpark" % "1.0"

Maven

In your pom.xml, add: 
<dependencies>
  <!-- list of dependencies -->
  <dependency>
    <groupId>FurongHuang</groupId>
    <artifactId>SpectralLDA-TensorSpark</artifactId>
    <version>1.0</version>
  </dependency>
</dependencies>
<repositories>
  <!-- list of other repositories -->
  <repository>
    <id>SparkPackagesRepo</id>
    <url>https://repos.spark-packages.org/</url>
  </repository>
</repositories>

Releases

Version: 1.0 ( 7007a7 | zip | jar ) / Date: 2016-12-04 / License: Apache-2.0 / Scala version: 2.11