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The Knowledge Flow Interface
Introduction In the knowledge flow users select Weka components from a toolbar, place them on a layout canvas, and connect them into a directed graph that processes and analyzes data In helps in visualizing the flow of data
Introduction
Demonstration We will build an ARFF loader that performs a cross validation using J48 Steps: From the Data Source tab select an ARFF loader and configure it To specify which attribute is the class we use ClassAssigner object from Evaluation tab Connect the DataSource and ClassAssigner by right clicking on DataSource Choose the class from ClassAssigner by right clicking on it and selecting the Configure option
Demonstration To use cross validation, select it from  Evaluation tab Connect the output of ClassAssigner to CrossValidationFoldMaker Now select a J48 from the Classifiers tab and connect  Connect J48 to CrossValidationFoldMaker first by training set and then by test set The next step is to select a ClassifierPerformanceEvaluator from the Evaluation panel and connect J48 to it by selecting the batchClassifier entry from the pop-up menu for J48 Finally, from the Visualization toolbar we place a TextViewer component on the canvas.
Demonstration Till now
Demonstration To start the process right click ARFFLoader and click Start loading Add a graph viewer and connect it to J48 ‘s graph output to see a graphical representation of the trees produced for each fold of the cross-validation Once you have redone the cross-validation with this extra component in place, selecting Show results from its pop-up menu produces a list of trees, one for each cross-validation fold
Demonstration
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WEKA: The Knowledge Flow Interface

  • 1. The Knowledge Flow Interface
  • 2. Introduction In the knowledge flow users select Weka components from a toolbar, place them on a layout canvas, and connect them into a directed graph that processes and analyzes data In helps in visualizing the flow of data
  • 4. Demonstration We will build an ARFF loader that performs a cross validation using J48 Steps: From the Data Source tab select an ARFF loader and configure it To specify which attribute is the class we use ClassAssigner object from Evaluation tab Connect the DataSource and ClassAssigner by right clicking on DataSource Choose the class from ClassAssigner by right clicking on it and selecting the Configure option
  • 5. Demonstration To use cross validation, select it from Evaluation tab Connect the output of ClassAssigner to CrossValidationFoldMaker Now select a J48 from the Classifiers tab and connect Connect J48 to CrossValidationFoldMaker first by training set and then by test set The next step is to select a ClassifierPerformanceEvaluator from the Evaluation panel and connect J48 to it by selecting the batchClassifier entry from the pop-up menu for J48 Finally, from the Visualization toolbar we place a TextViewer component on the canvas.
  • 7. Demonstration To start the process right click ARFFLoader and click Start loading Add a graph viewer and connect it to J48 ‘s graph output to see a graphical representation of the trees produced for each fold of the cross-validation Once you have redone the cross-validation with this extra component in place, selecting Show results from its pop-up menu produces a list of trees, one for each cross-validation fold
  • 9. Visit more self help tutorials Pick a tutorial of your choice and browse through it at your own pace. The tutorials section is free, self-guiding and will not involve any additional support. Visit us at www.dataminingtools.net