Hitachi Vantara Pentaho Community Wiki
Child pages
  • Weka Execution in Hadoop

Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.
Comment: Migration of unmigrated content due to installation of a new plugin
Include Page
Labs Production
Labs Production

Excerpt

A recipe for executing Weka in Hadoop.

Project Info

This package for Weka >= 3.7.10 provides several jobs for executing learning tasks inside of Hadoop. These include:

  1. Determining ARFF meta data and summary statisitics
  2. Computing a correlation or covariance matrix
  3. Training a Weka classifier or regressor
  4. Generating randomly shuffled (and stratified) input data chunks
  5. Evaluating a Weka classifier or regressor via cross-validation or a hold-out set
  6. Scoring using a training classifier or regressor

A full-featured command line interface is available along with GUI Knowledge Flow components for job orchestration. Predictive models learned in Hadoop are fully compatible with Pentaho Data Integration's "Weka Scoring" transformation step.

More information on what is available in the distributed Weka package, and how it is implemented, can be found in a three part blog posting:

Jira Issues
columnskey;fixVersion;summary;status;assignee;updated
anonymoustrue
urlhttp://jira.pentaho.com/sr/jira.issueviews:searchrequest-xml/temp/SearchRequest.xml?jqlQuery=text+%7E+%22map-reduce%20weka%22&tempMax=1000

Try it out!

Open Weka's package manager (GUIChooser->Tools->Package manager) and install "distributedWekaHadoop".

Wiki Markup
{scrollbar}