Machine Learning with WEKA

Bernhard Pfahringer (based on material by Eibe Frank, Mark Hall, and Peter Reutemann)

Department of Computer Science University of Waikato, New Zealand


WEKA : A Machine Learning Toolkit


The Explorer
- Classification and Regression
- Clustering
- Association Rules
- Attribute Selection
- Data Visualization


The Experimenter
The Knowledge Flow GUI
Other Utilities
Conclusions


WEKA: the software

nMachine learning/data mining software written in Java (distributed under the GNU Public License)

nUsed for research, education, and applications

nComplements “Data Mining” by Witten & Frank

nMain features:

uComprehensive set of data pre-processing tools, learning algorithms and evaluation methods

uGraphical user interfaces (incl. data visualization)

uEnvironment for comparing learning algorithms

WEKA: versions

nThere are several versions of WEKA:

uWEKA 3.4: “book version” compatible with description in data mining book

uWEKA 3.5.5: “development version” with lots of improvements

nThis talk is based on a nightly snapshot of WEKA 3.5.5 (12-Feb-2007)

WEKA only deals with “flat” files

@relation heart-disease-simplified

@attribute age numeric (numeric attribute)

@attribute sex { female, male} (nominal attribute)

@attribute chest_pain_type { typ_angina, asympt, non_anginal, atyp_angina}

@attribute cholesterol numeric

@attribute exercise_induced_angina { no, yes}

@attribute class { present, not_present} (Flat file in ARFF format)

@data

63,male,typ_angina,233,no,not_present

67,male,asympt,286,yes,present

67,male,asympt,229,yes,present

38,female,non_anginal,?,no,not_present

...

java weka.gui.GUIChooser

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