1. WEKA

2. Copyright: Martin Kramer (mkramer@wxs.nl)
Weka: the bird
Copyright: Martin Kramer
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University of Waikato

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6. Hamilton
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University of Waikato

7. WEKA: the software Waikato Environment for Knowledge Analysis
Collection of state-of-the-art machine learning algorithms and data processing tools implemented in Java
Released under the GPL
Support for the whole process of experimental data mining
Preparation of input data
Statistical evaluation of learning schemes
Visualization of input data and the result of learning
Used for education, research and applications
Complements “Data Mining” by Witten & Frank
9/22/2018
University of Waikato

8. Main Features 49 data preprocessing tools
76 classification/regression algorithms
8 clustering algorithms
15 attribute/subset evaluators + 10 search algorithms for feature selection
3 algorithms for finding association rules
3 graphical user interfaces
“The Explorer” (exploratory data analysis)
“The Experimenter” (experimental environment)
“The KnowledgeFlow” (new process model inspired interface)
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University of Waikato

9. History Project funded by the NZ government since 1993
Develop state-of-the art workbench of data mining tools
Explore fielded applications
Develop new fundamental methods
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University of Waikato

10. History - timeline Late 1992 - funding was applied for by Ian Witten
development of the interface and infrastructure
WEKA acronym coined by Geoff Holmes
WEKA’s file format “ARFF” was created by Andrew Donkin
ARFF was rumored to stand for Andrew’s Ridiculous File Format
Sometime in first internal release of WEKA
TCL/TK user interface + learning algorithms written mostly in C
Very much beta software
Changes for the b1 release included (among others):
“Ambiguous and Unsupported menu commands removed.”
“Crashing processes handled (in most cases :-)”
October first public release of WEKA (v 2.1)
9/22/2018
University of Waikato

11. History - timeline July 1997 - WEKA 2.2
Schemes: 1R, T2, K*, M5, M5Class, IB1-4, FOIL, PEBLS, support for C5
Included a facility (based on unix makefiles) for configuring and running large scale experiments
Early decision was made to rewrite WEKA in Java
Originated from code written by Eibe Frank for his PhD
Originally codenamed JAWS (JAva Weka System)
May WEKA 2.3
Last release of the TCL/TK-based system
Mid WEKA 3 (100% Java) released
Version to complement the Data Mining book
Development version (including GUI)
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University of Waikato

12. Back then…
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University of Waikato

14. Today:

15. Explorer: pre-processing the data
Data can be imported from a file in various formats: ARFF, CSV, C4.5, binary
Data can also be read from a URL or from an SQL databases using JDBC
Pre-processing tools in WEKA are called “filters”
WEKA contains filters for:
Discretization, normalization, resampling, attribute selection, attribute combination, …
9/22/2018
University of Waikato

16. Explorer: Building classification models
“Classifiers” in WEKA are models for predicting nominal or numeric quantities
Implemented schemes include:
Decision trees and lists, instance-based classifiers, support vector machines, multi-layer perceptrons, logistic regression, Bayes’ nets, …
“Meta”-classifiers include:
Bagging, boosting, stacking, error-correcting output codes, data cleansing, …
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University of Waikato

17. Explorer: classification
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18. Explorer: classification
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19. Explorer: classification
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20. Explorer: classification
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21. Explorer: classification
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22. Explorer: classification
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23. Explorer: classification
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24. Explorer: classification
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25. Explorer: classification
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26. KnowledgeFlow: process flows
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University of Waikato

27. KnowledgeFlow: batch processing
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University of Waikato

28. KnowledgeFlow: batch processing
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University of Waikato

29. KnowledgeFlow: incremental processing
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30. Experimenter
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31. Experimenter
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32. Experimenter
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University of Waikato

33. Impact - downloads
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University of Waikato

34. Projects based on WEKA Incorporate/wrap WEKA Extend/modify WEKA
GRB Tool Shed - a tool to aid gamma ray burst research
YALE - facility for large scale ML experiments
GATE - NLP workbench with a WEKA interface
Judge - document clustering and classification
Extend/modify WEKA
BioWeka - extension library for knowledge discovery in biology
WekaMetal - meta learning extension to WEKA
Weka-Parallel - parallel processing for WEKA
Grid Weka - grid computing using WEKA
Weka-CG - computational genetics tool library
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University of Waikato

35. The WEKA Project Today FRST funding for the next two years
Goal of the project remains the same
People
6 staff
2 postdocs
3 PhD students
3 MSc students
2 research programmers
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University of Waikato

36. The Future Continue to develop and support WEKA
MOA (Massive Online Analysis)
Framework that supports learning from data streams
Facilities for data generation, experimental analysis, learning algorithms, etc.
The Moa (another native NZ bird) is not only flightless, like the Weka, but also extinct
First public release, probably this Christmas, or perhaps Thanksgiving (as it’s just another turkey)
MILK
Multi-Instance Learning Kit
Proper
Propositionalization toolbox for WEKA
9/22/2018
University of Waikato