Slide 1OutlineWhat’s WekaWeka HomepageInstallation WekaMain FeaturesTake a tour Getting startTake a tour Weka Explorer ScreenshotTake a tourTake a tour FilterTake a tour 2D VisualizationTake a tour Classifier - 1Take a tour Classifier - 2Take a tour Classifier - 3Input File: .arff FormatInput File: .cvs FormatOutput Text-based resultsOutput Text-based results - exampleOutput Graphical-based resultsSlide 20Florida International UniversityCOP 4770Introduction of Weka Introduction of WekaOutlineIntroductionTake a tourInput & output formatIntroduction of WekaWhat’s WekaWaikato Environment for Knowledge Analysis (WEKA)Developed by the Department of Computer Science, University of Waikato, New ZealandMachine learning/data mining software written in Java (distributed under the GNU Public License)Used for research, education, and applicationsIntroduction of WekaWeka Homepagehttp://www.cs.waikato.ac.nz/ml/weka/To download WEKA 3.6.3:http://sourceforge.net/projects/weka/files/weka-3-6-windows/3.6.3/weka-3-6-3.exe/downloadIntroduction of WekaInstallation WekaTo run:weka-3-6-3.exeIntroduction of WekaMain Features Schemes for classification include: decision trees, rule learners, naive Bayes, decision tables, locally weighted regression, SVMs, instance-based learners, logistic regression, voted perceptrons, multi-layer perceptron Schemes for numeric prediction include: linear regression, model tree generators, locally weighted regression, instance-based learners, decision tables, multi-layer perceptron Meta-schemes include: Bagging, boosting, stacking, regression via classification, classification via regression, cost sensitive classification Schemes for clustering:EM and CobwebSchemes for feature selection:Ranker….Introduction of WekaTake a tourGetting startStart All Programs Weka 3.6.3 Weka 3.6 Click to Start a Tour!Introduction of WekaTake a tour Weka Explorer ScreenshotFilterLoadFeature InfoLabel InfoIntroduction of WekaTake a tourClick “Open file” ;Choose “Weka-3.6/data/*.arff”;Click “Open”. Introduction of WekaTake a tour FilterFilters can be used to change data files;AttributeSelection lets you select a set of attributes;Other filtersDiscretize: Discretizes a range of numeric attributes in the dataset into nominal attributes;NominalToBinary: Converts nominal attributes into binary ones, replacing each attribute with k values with k-1 new binary attributes;…Introduction of WekaTake a tour2D Visualization Visualize AttributesIntroduction of WekaTake a tour Classifier - 1Introduction of WekaTake a tour Classifier - 2Single Click!Introduction of WekaTake a tour Classifier - 3Introduction of WekaInput File: .arff Format Detail: http://www.cs.waikato.ac.nz/~ml/weka/arff.htmlRequire declarations of @RELATION, @ATTRIBUTE and @DATA @RELATION declaration associates a name with the dataset@ATTRIBUTE declaration specifies the name and type of an attribute@DATA declaration is a single line denoting the start of the data segmentIntroduction of WekaInput File: .cvs FormatIntroduction of WekaOutputText-based resultsRun Information;Summary of model;Statistics of training data;Predictions of test data;Type of sampling;Confusing Matrix;Detailed Accuracy by class;Entropy evaluation measures;…Introduction of WekaOutputText-based results - exampleclassifyResultExample.txtIntroduction of WekaOutputGraphical-based resultsIntroduction of WekaAny questions??Introduction of
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