Training_annexe

Parameters for manual experiment

public static void main(String[] args) {
    String signature = null;  // reserve

    // open indexer
    id = new IdxStructure("QUERY", new ConfigurationForCat()); 
    id.Statistic.global();  // get statistics

    // define path to catalog
    String fntrain = SenseOS.getMYCLASS_ROOT() + "MYCLASS_MODEL/sample/langdetect/corpus_dgt2014.cat";
    String fntest = SenseOS.getMYCLASS_ROOT() + "MYCLASS_MODEL/sample/langdetect/EMPTY.cat";

    // load catalog at the specified level (2 char codification in this case)
    NNBottomGroup BootGroup = new NNBottomGroup(id, fntrain, fntest, 2, false, false);

    // initialise the neural network ...
    NNOneN.init(signature, BootGroup, id, NNOneN.NORMALISED, NNOneN.SDF_SQUARE);

    // initialise the neural network ...
    Experiment x = new Experiment(

         // define filename and folder to store result
            "worddetect", // String experimentName,
            SenseOS.getMYCLASS_ROOT() + "MYCLASS_MODEL/experiment/langdetect/", // String pathfileSave,

         // define process parameter
            8, //  number of cores ,
            true, // store BOW in memory,

         // parameters for the training
            2,// train at this category level,
            "", // only for this sub-class,

        // parameters for the algorithm
            5, // int repeatK,
            1000, // float qlevel,
            1.06f, // float add,
            2, // int minocc,
            100000000, // int maxocc,
            300, // float deltamin,
            300, // float deltamax,
            false, // boolean verbosetrain,

        // parameters for the test
            true, // boolean testtrain,
            80, // int trainpart,

        // TEST -- parameters for the test
            3, // int Nfirst,
            true, // boolean maintest,
            true, // boolean maintestGroupdetail,
            false, // boolean maintestDocumentdetail,
            true, // boolean multitest,
            true, // boolean multitestGroupdetail ,
            false // boolean multitestOtherdetail 
            );
    x.doIt();

  // display a Confusion Matrix
  NNOneN.ConfusionMatrix(false);

  // display top features
  NNOneN.explainGroup(20, true);

}