an introduction to weka with demos - university of...
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An Introduction to Weka with Demos
Tomasz Oliwa
Ph.D., Computer Science, The University of Georgia, USA
Dipl.-Inform., University of Koblenz-Landau, Germany..
Lecture in CSCI/ARTI 8950 Machine LearningSlides at: http://www.cs.uga.edu/~tomasz/weka2013fall/
September 5, 2013
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Weka Software
The Weka machine learning/data mining suite:
Rich collection of preprocessing, (un)/supervisedlearning and evaluation algorithms
Accessible GUI
Java, Free software (GPL):http://www.cs.waikato.ac.nz/~ml/weka/
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Attribute-Relation File Format (ARFF)
@relation weather
@attribute outlook sunny, overcast, rainy
@attribute temperature real
@attribute humidity real
@attribute windy TRUE, FALSE
@attribute play yes, no
@data
sunny,85,85,FALSE,no
sunny,80,90,TRUE,no
overcast,83,86,FALSE,yes
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Weka Modes1 Explorer: Direct application and visualizations2 Experimenter: Run & compare algorithms3 Knowledge Flow: Visual composition of workflow4 Simple CLI: Command line interface5 Source code: Weka classes in Java code
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Weka GUI Chooser
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Preprocessing
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Preprocessing - Load Data
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Preprocessing - Data Overview
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Preprocessing - Visualize All
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Classification
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Classification Results
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Classification Results - DT
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Clustering Results
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Attribute Selection Results
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Demos
Demo time:
Preprocessing
Classification
Regression
Clustering
Feature Selection
Experimenter
Source code import
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Take Home Message
Weka is a powerful machine learning suite:
Explorer: Intuitive suite with result visualizations
Experimenter: Batch perform statistical tests onresults
Source code: Directly import Weka classes in yourprograms
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Questions
Thanks for your attention!
Do you have any questions?
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References and Tutorials
Weka: http://www.cs.waikato.ac.nz/~ml/weka/
Weka Wiki: http://weka.wikispaces.com/
IBM Weka Tutorials:
Introduction and Regression:http://www.ibm.com/developerworks/opensource/
library/os-weka1/index.html
Classification and clustering:http://www.ibm.com/developerworks/opensource/
library/os-weka2/index.html
Nearest Neighbor and server-side library:http://www.ibm.com/developerworks/opensource/
library/os-weka3/index.html
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