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WEKA: A Practical Machine Learning Tool WEKA:A Practical Machine Learning Tool WEKA: A Practical Machine Learning Tool Contents 1.Introduction to Weka 2.Explorer 3.Other three main tools 4.Conclusions 5.Reference WEKA: A Practical Machine Learning Tool Introduction – What is Weka? In nature: A flightless bird with an inquisitive nature found only on the islands of New Zealand. Actually: A practical machine learning tool developed by the University of Waikato in New Zealand. It is short for Waikato Environment for Knowledge Analysis. Definition: A collection of machine learning algorithms for data mining tasks. Language: It is written in Java and runs on almost any platform. Usage: The algorithms can either be applied: (1) directly to a dataset (without writing any codes); (2) called from your own Java code. WEKA: A Practical Machine Learning Tool Introduction – Weka consists of Explorer Experimenter Knowledge flow Simple Command Line Interface(CLI) Other tools and Visualization Java interface WEKA: A Practical Machine Learning Tool Explorer WEKA’s main graphical user interface Gives access to all its facilities using menu selection and form filling.(Data-Preprocess/Classify/Cluster/Associate/Select Attributes/Visualize) 1.Data 2. Operations of Explorer with a Classification example. WEKA: A Practical Machine Learning Tool Explorer – Data(1) From files: CSV, ARFF, C4.5…(no *.xls) Data loaded from URL or DB Attribute-Class Attribute Instance *.xls Instances Tips:weather.arff ( C:/Program Files/Weka/data/ ) *.csv WEKA: A Practical Machine Learning Tool Explorer – Data(2) ARFF(Attribute-Relation File Format) @relation <relation-name> @attribute <attribute-name> <datatype> ①numeric (real or integer numbers) ②<nominal-specification> ③string ④date [<date-format>] @data % notes More details: http://www.cs.waikato.ac.nz/ ~ml/weka/arff.html WEKA: A Practical Machine Learning Tool Explorer – Operations with an example Input data Data preprocess Choose classifier Test options Run Result analysis WEKA: A Practical Machine Learning Tool Explorer Summary Statistics Input data Select an attribute Visualization WEKA: A Practical Machine Learning Tool Explorer Weka Filter Tune Parameters Apply the Filter Select a Filter WEKA: A Practical Machine Learning Tool Explorer Tune Parameters Results Select a Classifier Decide how to evaluate Model list WEKA: A Practical Machine Learning Tool Right-click on model to get Menu (save, visualize, etc) WEKA: A Practical Machine Learning Tool WEKA: A Practical Machine Learning Tool Others – Experimenter Comparing different learning algorithms ------on different datasets ------with various parameter settings ------and analyzing the performance statistics Click it for Experimenter WEKA: A Practical Machine Learning Tool Others – KnowledgeFlow The KnowledgeFlow provides an alternative to the Explorer as a graphical front end to Weka's core algorithms. The KnowledgeFlow is a work in progress so some of the functionality from the Explorer is not yet available. Click it for KnowledgyFlow WEKA: A Practical Machine Learning Tool Others – Simple command line interface All implementations of the algorithms have a uniform commandline interface. java weka.classifiers.trees.J48 -t weather.arff Click it for Simple CLI WEKA: A Practical Machine Learning Tool Conclusions 1.Explorer: Input data Data preprocess Choose classifier Test options Run Result analysis 2.Experimenter: It is necessary for further studies. 3.Make full use of: 1. Java tips; 2. WekaManual.pdf; (C:/Program Files/Weka/ ) 3. Play it yourself! WEKA: A Practical Machine Learning Tool Reference Mitchell, T. Machine Learning, 1997 McGraw Hill. Ian H. Witten, Eibe Frank, Len Trigg, Mark Hall, Geoffrey Holmes, and Sally Jo Cunningham (1999). Weka: Practical machine learning tools and techniques with Java implementations. Ian H. Witten, Eibe Frank (2005). Data Mining: Practical Machine Learning Tools and Techniques (Second Edition, 2005). San Francisco: Morgan Kaufmann Weka Homepage: http://www.cs.waikato.ac.nz/~ml/weka/ Wekawiki: http://weka.wikispaces.com/ Weka on SourceForge.net: http://sourceforge.net/projects/weka WekaManual.pdf (C:\Program Files\Weka-3-6\WekaManual.pdf)