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Machine Learning with WEKA. WEKA: the bird Copyright: Martin Kramer

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1 Machine Learning with WEKA

2 WEKA: the bird Copyright: Martin Kramer (mkramer@wxs.nl)

3 WEKA: the software Machine learning/data mining software written in Java (distributed under the GNU Public License) Used for research, education, and applications Complements “Data Mining” by Witten & Frank Main features: –Comprehensive set of data pre-processing tools, learning algorithms and evaluation methods –Graphical user interfaces (incl. data visualization) –Environment for comparing learning algorithms

4 WEKA: versions There are several versions of WEKA: –WEKA 3.0: “book version” compatible with description in data mining book –WEKA 3.2: “GUI version” adds graphical user interfaces (book version is command-line only) –WEKA 3.3: “development version” with lots of improvements This talk is based on the latest snapshot of WEKA 3.3 (soon to be WEKA 3.4)

5 @relation heart-disease-simplified @attribute age numeric @attribute sex { female, male} @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} @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... WEKA only deals with “ flat ” files

6 @relation heart-disease-simplified @attribute age numeric @attribute sex { female, male} @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} @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... WEKA only deals with “ flat ” files

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10 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 database (using JDBC) Pre-processing tools in WEKA are called “filters” WEKA contains filters for: –Discretization, normalization, resampling, attribute selection, transforming and combining attributes, …

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12 Check irisv1.txt 7. Attribute Information: % 1. sepal length in cm ( 萼片 ) % 2. sepal width in cm % 3. petal length in cm ( 花瓣 ) % 4. petal width in cm % 5. class: % -- Iris Setosa % -- Iris Versicolour % -- Iris Virginica

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