Examples of org.encog.ml.MLRegression

org.encog.ml.MLRegression
Defines a Machine Learning Method that supports regression. Regression takes an input and produces numeric output. Function approximation uses regression. Contrast this to classification, which uses the input to assign a class.

   * Calculate the genome's score.
   * @param genome The genome to calculate for.
   * @return The calculated score.
   */
  public final double calculateScore(final Genome genome) {
    final MLRegression network = (MLRegression) genome.getOrganism();
    return this.calculateScore.calculateScore(network);
  }

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    final File resourceFile = getScript().resolveFilename(resourceID);


    final File outputFile = getAnalyst().getScript().resolveFilename(
        outputID);


    final MLRegression method = (MLRegression) EncogDirectoryPersistence
        .loadObject(resourceFile);


    final boolean headers = getScript().expectInputHeaders(evalID);


    final AnalystEvaluateRawCSV eval = new AnalystEvaluateRawCSV();

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    if( !(m instanceof MLRegression) ) {
      throw new AnalystError("The evaluate raw command can only be used with regression.");
    }


    final MLRegression method = (MLRegression)m;


    final boolean headers = getScript().expectInputHeaders(evalID);


    final AnalystEvaluateRawCSV eval = new AnalystEvaluateRawCSV();
    eval.setScript(getScript());

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Related Classes of org.encog.ml.MLRegression

org.encog.app.analyst.commands.CmdEvaluateRaw

org.encog.neural.networks.training.genetic.GeneticScoreAdapter

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