Examples with VectorAssembler com.alibaba.alink.pipeline.dataproc.vector.VectorAssembler used on opensource projects

Example 1 with VectorAssembler

use of com.alibaba.alink.pipeline.dataproc.vector.VectorAssembler in project Alink by alibaba.

the class ModelSaveAndLoadTest method testSaveLoadSave.

@Test
public void testSaveLoadSave() throws Exception {
    VectorAssembler va = new VectorAssembler().setSelectedCols(Iris.getFeatureColNames()).setOutputCol("features");
    MultilayerPerceptronClassifier classifier = new MultilayerPerceptronClassifier().setVectorCol("features").setLabelCol(Iris.getLabelColName()).setLayers(new int[] { 4, 5, 3 }).setMaxIter(30).setPredictionCol("pred_label").setPredictionDetailCol("pred_detail").setReservedCols(Iris.getLabelColName());
    Pipeline pipeline = new Pipeline().add(va).add(classifier);
    PipelineModel model = PipelineModel.collectLoad(pipeline.fit(data).save());
    LocalPredictor localPredictor = model.collectLocalPredictor(data.getSchema());
    Row pred = localPredictor.map(Row.of(4.8, 3.4, 1.9, 0.2, "Iris-setosa"));
    Assert.assertEquals(pred.getArity(), 3);
}

Example 2 with VectorAssembler

use of com.alibaba.alink.pipeline.dataproc.vector.VectorAssembler in project Alink by alibaba.

the class PipelineModelTest method getPipeline.

protected Pipeline getPipeline() {
    // model mapper
    QuantileDiscretizer quantileDiscretizer = new QuantileDiscretizer().setNumBuckets(2).setSelectedCols("sepal_length");
    // SISO mapper
    Binarizer binarizer = new Binarizer().setSelectedCol("petal_width").setOutputCol("bina").setReservedCols("sepal_length", "petal_width", "petal_length", "category").setThreshold(1.);
    // MISO Mapper
    VectorAssembler assembler = new VectorAssembler().setSelectedCols("sepal_length", "petal_width").setOutputCol("assem").setReservedCols("sepal_length", "petal_width", "petal_length", "category");
    // Lda
    Lda lda = new Lda().setPredictionCol("lda_pred").setPredictionDetailCol("lda_pred_detail").setSelectedCol("category").setTopicNum(2).setRandomSeed(0);
    return new Pipeline().add(binarizer).add(assembler).add(quantileDiscretizer).add(lda);
}

Example 3 with VectorAssembler

use of com.alibaba.alink.pipeline.dataproc.vector.VectorAssembler in project Alink by alibaba.

the class PipelineSaveAndLoadTest method testSaveLoadSave.

@Test
public void testSaveLoadSave() throws Exception {
    VectorAssembler va = new VectorAssembler().setSelectedCols(Iris.getFeatureColNames()).setOutputCol("features");
    MultilayerPerceptronClassifier classifier = new MultilayerPerceptronClassifier().setVectorCol("features").setLabelCol(Iris.getLabelColName()).setLayers(new int[] { 4, 5, 3 }).setMaxIter(30).setPredictionCol("pred_label").setPredictionDetailCol("pred_detail").setReservedCols(Iris.getLabelColName());
    Pipeline pipeline = new Pipeline().add(va).add(classifier);
    Pipeline pipeline1 = Pipeline.collectLoad(pipeline.save());
    PipelineModel model = PipelineModel.collectLoad(pipeline1.fit(data).save());
    LocalPredictor localPredictor = model.collectLocalPredictor(data.getSchema());
    Row pred = localPredictor.map(Row.of(4.8, 3.4, 1.9, 0.2, "Iris-setosa"));
    Assert.assertEquals(pred.getArity(), 3);
}

Example 4 with VectorAssembler

use of com.alibaba.alink.pipeline.dataproc.vector.VectorAssembler in project Alink by alibaba.

the class PipelineSaveAndLoadTest method testNewSave.

@Test
public void testNewSave() throws Exception {
    VectorAssembler va = new VectorAssembler().setSelectedCols(Iris.getFeatureColNames()).setOutputCol("features");
    MultilayerPerceptronClassifier classifier = new MultilayerPerceptronClassifier().setVectorCol("features").setLabelCol(Iris.getLabelColName()).setLayers(new int[] { 4, 5, 3 }).setMaxIter(30).setPredictionCol("pred_label").setPredictionDetailCol("pred_detail").setReservedCols(Iris.getLabelColName());
    Pipeline pipeline = new Pipeline().add(va).add(classifier);
    PipelineModel model = pipeline.fit(data);
    BatchOperator<?> saved = model.save();
    PipelineModel modelLoaded = PipelineModel.collectLoad(saved);
    Assert.assertEquals(modelLoaded.transform(Iris.getBatchData()).count(), 150);
}

Example 5 with VectorAssembler

use of com.alibaba.alink.pipeline.dataproc.vector.VectorAssembler in project Alink by alibaba.

the class PipelineSaveAndLoadTest method testNestedSaveAndLoad.

@Test
public void testNestedSaveAndLoad() throws Exception {
    VectorAssembler va = new VectorAssembler().setSelectedCols(Iris.getFeatureColNames()).setOutputCol("features");
    MultilayerPerceptronClassifier classifier = new MultilayerPerceptronClassifier().setVectorCol("features").setLabelCol(Iris.getLabelColName()).setLayers(new int[] { 4, 5, 3 }).setMaxIter(2).setPredictionCol("pred_label").setPredictionDetailCol("pred_detail").setReservedCols(Iris.getLabelColName());
    Pipeline pipeline = new Pipeline().add(new Pipeline().add(va).add(classifier));
    Pipeline pipeline1 = Pipeline.collectLoad(pipeline.save());
    Assert.assertEquals(PipelineModel.collectLoad(pipeline1.fit(data).save()).transform(Iris.getBatchData()).count(), 150);
}