use of org.apache.ignite.ml.clustering.kmeans.KMeansModelFormat in project ignite by apache.
the class CollectionsTest method test.
/**
*/
@Test
@SuppressWarnings("unchecked")
public void test() {
test(new VectorizedViewMatrix(new DenseMatrix(2, 2), 1, 1, 1, 1), new VectorizedViewMatrix(new DenseMatrix(3, 2), 2, 1, 1, 1));
specialTest(new ManhattanDistance(), new ManhattanDistance());
specialTest(new HammingDistance(), new HammingDistance());
specialTest(new EuclideanDistance(), new EuclideanDistance());
FeatureMetadata data = new FeatureMetadata("name2");
data.setName("name1");
test(data, new FeatureMetadata("name2"));
test(new DatasetRow<>(new DenseVector()), new DatasetRow<>(new DenseVector(1)));
test(new LabeledVector<>(new DenseVector(), null), new LabeledVector<>(new DenseVector(1), null));
test(new Dataset<DatasetRow<Vector>>(new DatasetRow[] {}, new FeatureMetadata[] {}), new Dataset<DatasetRow<Vector>>(new DatasetRow[] { new DatasetRow() }, new FeatureMetadata[] { new FeatureMetadata() }));
test(new LogisticRegressionModel(new DenseVector(), 1.0), new LogisticRegressionModel(new DenseVector(), 0.5));
test(new KMeansModelFormat(new Vector[] {}, new ManhattanDistance()), new KMeansModelFormat(new Vector[] {}, new HammingDistance()));
test(new KMeansModel(new Vector[] {}, new ManhattanDistance()), new KMeansModel(new Vector[] {}, new HammingDistance()));
test(new SVMLinearClassificationModel(null, 1.0), new SVMLinearClassificationModel(null, 0.5));
test(new ANNClassificationModel(new LabeledVectorSet<>(), new ANNClassificationTrainer.CentroidStat()), new ANNClassificationModel(new LabeledVectorSet<>(1, 1), new ANNClassificationTrainer.CentroidStat()));
test(new ANNModelFormat(1, new ManhattanDistance(), false, new LabeledVectorSet<>(), new ANNClassificationTrainer.CentroidStat()), new ANNModelFormat(2, new ManhattanDistance(), false, new LabeledVectorSet<>(), new ANNClassificationTrainer.CentroidStat()));
}
use of org.apache.ignite.ml.clustering.kmeans.KMeansModelFormat in project ignite by apache.
the class LocalModelsTest method importExportKMeansModelTest.
/**
*/
@Test
public void importExportKMeansModelTest() throws IOException {
executeModelTest(mdlFilePath -> {
KMeansModel mdl = getClusterModel();
Exporter<KMeansModelFormat, String> exporter = new FileExporter<>();
mdl.saveModel(exporter, mdlFilePath);
KMeansModelFormat load = exporter.load(mdlFilePath);
Assert.assertNotNull(load);
KMeansModel importedMdl = new KMeansModel(load.getCenters(), load.getDistance());
Assert.assertEquals("", mdl, importedMdl);
return null;
});
}
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