Examples with KMeansParams org.opensearch.ml.common.parameter.KMeansParams used on opensource projects

Example 6 with KMeansParams

use of org.opensearch.ml.common.parameter.KMeansParams in project ml-commons by opensearch-project.

the class MLEngineTest method trainKMeansModel.

private Model trainKMeansModel() {
    KMeansParams parameters = KMeansParams.builder().centroids(2).iterations(10).distanceType(KMeansParams.DistanceType.EUCLIDEAN).build();
    DataFrame trainDataFrame = constructKMeansDataFrame(100);
    MLInputDataset inputDataset = DataFrameInputDataset.builder().dataFrame(trainDataFrame).build();
    Input mlInput = MLInput.builder().algorithm(FunctionName.KMEANS).parameters(parameters).inputDataset(inputDataset).build();
    return MLEngine.train(mlInput);
}

Example 7 with KMeansParams

use of org.opensearch.ml.common.parameter.KMeansParams in project ml-commons by opensearch-project.

the class MLPredictionTaskRequestTest method writeTo_Success.

@Test
public void writeTo_Success() throws IOException {
    MLPredictionTaskRequest request = MLPredictionTaskRequest.builder().mlInput(mlInput).build();
    BytesStreamOutput bytesStreamOutput = new BytesStreamOutput();
    request.writeTo(bytesStreamOutput);
    request = new MLPredictionTaskRequest(bytesStreamOutput.bytes().streamInput());
    assertEquals(FunctionName.KMEANS, request.getMlInput().getAlgorithm());
    KMeansParams params = (KMeansParams) request.getMlInput().getParameters();
    assertEquals(1, params.getCentroids().intValue());
    MLInputDataset inputDataset = request.getMlInput().getInputDataset();
    assertEquals(MLInputDataType.DATA_FRAME, inputDataset.getInputDataType());
    DataFrame dataFrame = ((DataFrameInputDataset) inputDataset).getDataFrame();
    assertEquals(1, dataFrame.size());
    assertEquals(1, dataFrame.columnMetas().length);
    assertEquals("key1", dataFrame.columnMetas()[0].getName());
    assertEquals(ColumnType.DOUBLE, dataFrame.columnMetas()[0].getColumnType());
    assertEquals(1, dataFrame.getRow(0).size());
    assertEquals(2.00, dataFrame.getRow(0).getValue(0).getValue());
    assertNull(request.getModelId());
}

Example 8 with KMeansParams

use of org.opensearch.ml.common.parameter.KMeansParams in project ml-commons by opensearch-project.

the class KMeansTest method trainAndPredict.

@Test
public void trainAndPredict() {
    KMeansParams parameters = KMeansParams.builder().distanceType(KMeansParams.DistanceType.EUCLIDEAN).iterations(10).centroids(2).build();
    KMeans kMeans = new KMeans(parameters);
    MLPredictionOutput output = (MLPredictionOutput) kMeans.trainAndPredict(trainDataFrame);
    DataFrame predictions = output.getPredictionResult();
    Assert.assertEquals(trainSize, predictions.size());
    predictions.forEach(row -> Assert.assertTrue(row.getValue(0).intValue() == 0 || row.getValue(0).intValue() == 1));
    parameters = parameters.toBuilder().distanceType(KMeansParams.DistanceType.COSINE).build();
    kMeans = new KMeans(parameters);
    output = (MLPredictionOutput) kMeans.trainAndPredict(trainDataFrame);
    predictions = output.getPredictionResult();
    Assert.assertEquals(trainSize, predictions.size());
    parameters = parameters.toBuilder().distanceType(KMeansParams.DistanceType.L1).build();
    kMeans = new KMeans(parameters);
    output = (MLPredictionOutput) kMeans.trainAndPredict(trainDataFrame);
    predictions = output.getPredictionResult();
    Assert.assertEquals(trainSize, predictions.size());
}

Example 9 with KMeansParams

use of org.opensearch.ml.common.parameter.KMeansParams in project ml-commons by opensearch-project.

the class RestMLTrainAndPredictIT method trainAndPredictKmeansWithEmptyParam.

private void trainAndPredictKmeansWithEmptyParam() throws IOException {
    KMeansParams params = KMeansParams.builder().build();
    trainAndPredictKmeansWithParmas(params, clusterCount -> assertEquals(2, clusterCount.size()));
}

Example 10 with KMeansParams

use of org.opensearch.ml.common.parameter.KMeansParams in project ml-commons by opensearch-project.

the class RestMLTrainAndPredictIT method trainAndPredictKmeansWithCustomParam.

private void trainAndPredictKmeansWithCustomParam() throws IOException {
    KMeansParams params = KMeansParams.builder().centroids(3).build();
    trainAndPredictKmeansWithParmas(params, clusterCount -> assertTrue(clusterCount.size() >= 2));
}