Pentaho Data Mining - Weka

Pentaho Data Mining - Weka

Summary

Description

Data Mining is the process of running data through sophisticated algorithms to uncover meaningful patterns and correlations that may otherwise be hidden. Pentaho Data Mining incorporates Weka, a collection of machine learning algorithms applied to data mining tasks. These algorithms are combined with OLAP technologies to merge machine-intelligent data analysis with business process solutions. Data mining tools can analyze historical data to create predictive models of business processes.

All the features of the BI Platform will be supported including web services, workflow integration, security, auditing, scheduling, navigation, portal integration, workbench-based designer and administration tools.

Issues: Due

  • New Feature DATAMINING-270 Hellinger Distance
  • New Feature DATAMINING-41 Execution of PDI (Kettle) transforms in KnowledgeFlow
  • Improvement DATAMINING-53 Ability to output sparse instances from the ArffOutput step

Issues: 30 Day Summary


Issues: 9 created and 11 resolved

Issues: Updated recently

  • Improvement DATAMINING-295 Last Sunday 6:34 PM Add an "InputMappedClassifier" that can wrap a classifier and map between the data structure used to learn the model and incoming test instances structure
  • Bug DATAMINING-296 Last Thursday 6:06 PM FilteredClassifier throws an exception if the filter does not make a test instance available immediately
  • New Feature DATAMINING-270 25/Aug/10 Hellinger Distance

Versions: Due

Activity Stream