X

More Data Mining with Weka

This course follows on from Data Mining with Weka and provides a deeper account of data mining tools and techniques. Again the emphasis is on principles and practical data mining using Weka, rather than mathematical theory or advanced details of particular algorithms. Students will work with multimillion-instance datasets, classify text, experiment with clustering, association rules, neural networks, and much more.

A new session starts on 3 October 2016, and the course will run in self-paced unsupported mode until 3rd January; whereupon Statements of Completion will be produced and mailed out. Students should have completed Data Mining with Weka, or have equivalent knowledge of the subject.

The course features:

Subscribe to the Announcements forum for updates and reminders.

Please read the Terms of Service and Participant Information Sheet before registering.

Prof Ian H. Witten
Department of Computer Science
University of Waikato

Schedule

  • Pre-course survey

  • Class 1 - Exploring Weka's interfaces, and working with big data

  • Class 2 - Discretization and text classification

  • Mid-course assessment

  • Class 3 - Classification rules, association rules, and clustering

  • Class 4 - Selecting attributes and counting the cost

  • Class 5 - Neural networks, learning curves, and performance optimization

  • Post-course assessment

  • Post-course survey