WEKA: The Experimenter

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Introduction to The Experimenter in Weka

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WEKA: The Experimenter

  1. 1. The Experimenter<br />
  2. 2. Introduction<br />The Experimenter enables you to set up large-scale experiments, start them running, leave them, and come back when they have finished and analyze the performance statistics that have been collected<br />They automate the experimental process<br />The statistics can be stored in ARFF format<br />It allows users to distribute the computing load across multiple machines using Java RMI<br />
  3. 3. Introduction<br />
  4. 4. Demonstration<br />We will compare the J48 decision tree method with the baseline methods OneR<br />Steps:<br />First click New to start a new experiment<br />Then, on the line below, select the destination for the results<br />Underneath, select the datasets<br />To the right of the datasets, select the algorithms to be tested. Click Add new to get a standard Weka object editor from which you can choose and configure a classifier. Repeat this operation to add the two classifiers<br />
  5. 5. Demonstration<br />To run the experiment click on the Run tab and then click on the Start button. The result will be stored on the output file<br />To analyze the two selected classifiers , go to the Analyse tab and click on Experiment<br />The symbol placed beside a result indicates that it is statistically better (v) or worse (*) than the baseline scheme<br />At the bottom of column 2 are counts (x/y/z) of the number of times the scheme was better than (x), the same as (y), or worse than (z) the baseline scheme on the datasets used in the experiment<br />
  6. 6. Demonstration<br />
  7. 7. Visit more self help tutorials<br />Pick a tutorial of your choice and browse through it at your own pace.<br />The tutorials section is free, self-guiding and will not involve any additional support.<br />Visit us at www.dataminingtools.net<br />

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