Examples with LinearSvm com.alibaba.alink.pipeline.classification.LinearSvm used on opensource projects

Example 1 with LinearSvm

use of com.alibaba.alink.pipeline.classification.LinearSvm in project Alink by alibaba.

the class Chap13 method c_3.

static void c_3() throws Exception {
    AkSourceBatchOp train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TRAIN_FILE);
    AkSourceBatchOp test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TEST_FILE);
    BatchOperator.setParallelism(1);
    new OneVsRest().setClassifier(new LogisticRegression().setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME)).setNumClass(10).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("OneVsRest - LogisticRegression"));
    new OneVsRest().setClassifier(new LinearSvm().setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME)).setNumClass(10).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("OneVsRest - LinearSvm"));
    BatchOperator.execute();
}

Example 2 with LinearSvm

use of com.alibaba.alink.pipeline.classification.LinearSvm in project Alink by alibaba.

the class Chap08 method c_8.

static void c_8() throws Exception {
    BatchOperator<?> train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TRAIN_FILE);
    BatchOperator<?> test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TEST_FILE);
    PipelineModel featureExpand = new Pipeline().add(new VectorAssembler().setSelectedCols(FEATURE_COL_NAMES).setOutputCol(VEC_COL_NAME + "_0")).add(new VectorPolynomialExpand().setSelectedCol(VEC_COL_NAME + "_0").setOutputCol(VEC_COL_NAME).setDegree(2)).fit(train_data);
    train_data = featureExpand.transform(train_data);
    test_data = featureExpand.transform(test_data);
    train_data.lazyPrint(1);
    new LinearSvm().setVectorCol(VEC_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).fit(train_data).transform(test_data).link(new EvalBinaryClassBatchOp().setPositiveLabelValueString("1").setLabelCol(LABEL_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).lazyPrintMetrics("LinearSVM"));
    new LogisticRegression().setVectorCol(VEC_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).fit(train_data).transform(test_data).link(new EvalBinaryClassBatchOp().setPositiveLabelValueString("1").setLabelCol(LABEL_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).lazyPrintMetrics("LogisticRegression"));
    new LogisticRegression().setOptimMethod(OptimMethod.Newton).setVectorCol(VEC_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).fit(train_data).transform(test_data).link(new EvalBinaryClassBatchOp().setPositiveLabelValueString("1").setLabelCol(LABEL_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).lazyPrintMetrics("LogisticRegression + OptimMethod.Newton"));
    BatchOperator.execute();
}

Example 3 with LinearSvm

use of com.alibaba.alink.pipeline.classification.LinearSvm in project Alink by alibaba.

the class Chap12 method c_4.

static void c_4() throws Exception {
    AkSourceBatchOp train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TRAIN_FILE);
    AkSourceBatchOp test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TEST_FILE);
    new OneVsRest().setClassifier(new LogisticRegression().setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME)).setNumClass(3).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("OneVsRest_LogisticRegression"));
    new OneVsRest().setClassifier(new GbdtClassifier().setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME)).setNumClass(3).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("OneVsRest_GBDT"));
    new OneVsRest().setClassifier(new LinearSvm().setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME)).setNumClass(3).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("OneVsRest_LinearSvm"));
    BatchOperator.execute();
}