Examples with SplitDataGenerator org.apache.ignite.ml.trees.SplitDataGenerator used on opensource projects

Example 1 with SplitDataGenerator

use of org.apache.ignite.ml.trees.SplitDataGenerator in project ignite by apache.

the class ColumnDecisionTreeTrainerBenchmark method testByGenStreamerLoad.

/**
 */
private void testByGenStreamerLoad(int ptsPerReg, HashMap<Integer, Integer> catsInfo, SplitDataGenerator<DenseLocalOnHeapVector> gen, Random rnd) {
    List<IgniteBiTuple<Integer, DenseLocalOnHeapVector>> lst = gen.points(ptsPerReg, (i, rn) -> i).collect(Collectors.toList());
    int featCnt = gen.featuresCnt();
    Collections.shuffle(lst, rnd);
    int numRegs = gen.regsCount();
    SparseDistributedMatrix m = new SparseDistributedMatrix(numRegs * ptsPerReg, featCnt + 1, StorageConstants.COLUMN_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
    IgniteFunction<DoubleStream, Double> regCalc = s -> s.average().orElse(0.0);
    Map<Integer, List<LabeledVectorDouble>> byRegion = new HashMap<>();
    SparseDistributedMatrixStorage sto = (SparseDistributedMatrixStorage) m.getStorage();
    long before = System.currentTimeMillis();
    X.println("Batch loading started...");
    loadVectorsIntoSparseDistributedMatrixCache(sto.cache().getName(), sto.getUUID(), gen.points(ptsPerReg, (i, rn) -> i).map(IgniteBiTuple::get2).iterator(), featCnt + 1);
    X.println("Batch loading took " + (System.currentTimeMillis() - before) + " ms.");
    for (IgniteBiTuple<Integer, DenseLocalOnHeapVector> bt : lst) {
        byRegion.putIfAbsent(bt.get1(), new LinkedList<>());
        byRegion.get(bt.get1()).add(asLabeledVector(bt.get2().getStorage().data()));
    }
    ColumnDecisionTreeTrainer<VarianceSplitCalculator.VarianceData> trainer = new ColumnDecisionTreeTrainer<>(2, ContinuousSplitCalculators.VARIANCE, RegionCalculators.VARIANCE, regCalc, ignite);
    before = System.currentTimeMillis();
    DecisionTreeModel mdl = trainer.train(new MatrixColumnDecisionTreeTrainerInput(m, catsInfo));
    X.println("Training took: " + (System.currentTimeMillis() - before) + " ms.");
    byRegion.keySet().forEach(k -> {
        LabeledVectorDouble sp = byRegion.get(k).get(0);
        Tracer.showAscii(sp.features());
        X.println("Predicted value and label [pred=" + mdl.apply(sp.features()) + ", label=" + sp.doubleLabel() + "]");
        assert mdl.apply(sp.features()) == sp.doubleLabel();
    });
}