Examples with GDBTrainer org.apache.ignite.ml.composition.boosting.GDBTrainer used on opensource projects

Example 6 with GDBTrainer

use of org.apache.ignite.ml.composition.boosting.GDBTrainer in project ignite by apache.

the class GDBOnTreesRegressionExportImportExample method main.

/**
 * Run example.
 *
 * @param args Command line arguments, none required.
 */
public static void main(String[] args) throws IOException {
    System.out.println();
    System.out.println(">>> GDB regression trainer example started.");
    // Start ignite grid.
    try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
        System.out.println(">>> Ignite grid started.");
        // Create cache with training data.
        CacheConfiguration<Integer, double[]> trainingSetCfg = createCacheConfiguration();
        IgniteCache<Integer, double[]> trainingSet = null;
        Path jsonMdlPath = null;
        try {
            trainingSet = fillTrainingData(ignite, trainingSetCfg);
            // Create regression trainer.
            GDBTrainer trainer = new GDBRegressionOnTreesTrainer(1.0, 2000, 1, 0.).withCheckConvergenceStgyFactory(new MeanAbsValueConvergenceCheckerFactory(0.001));
            // Train decision tree model.
            GDBModel mdl = trainer.fit(ignite, trainingSet, new DoubleArrayVectorizer<Integer>().labeled(Vectorizer.LabelCoordinate.LAST));
            System.out.println("\n>>> Exported GDB regression model: " + mdl.toString(true));
            predictOnGeneratedData(mdl);
            jsonMdlPath = Files.createTempFile(null, null);
            mdl.toJSON(jsonMdlPath);
            IgniteFunction<Double, Double> lbMapper = lb -> lb;
            GDBModel modelImportedFromJSON = GDBModel.fromJSON(jsonMdlPath).withLblMapping(lbMapper);
            System.out.println("\n>>> Imported GDB regression model: " + modelImportedFromJSON.toString(true));
            predictOnGeneratedData(modelImportedFromJSON);
            System.out.println(">>> GDB regression trainer example completed.");
        } finally {
            if (trainingSet != null)
                trainingSet.destroy();
            if (jsonMdlPath != null)
                Files.deleteIfExists(jsonMdlPath);
        }
    } finally {
        System.out.flush();
    }
}