Examples with EvalMultiClassBatchOp com.alibaba.alink.operator.batch.evaluation.EvalMultiClassBatchOp used on opensource projects

Example 1 with EvalMultiClassBatchOp

use of com.alibaba.alink.operator.batch.evaluation.EvalMultiClassBatchOp in project Alink by alibaba.

the class Chap12 method c_5.

static void c_5() throws Exception {
    AkSourceBatchOp train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TRAIN_FILE);
    AkSourceBatchOp test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TEST_FILE);
    new Softmax().setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).enableLazyPrintTrainInfo().enableLazyPrintModelInfo().fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("Softmax"));
    BatchOperator.execute();
}

Example 2 with EvalMultiClassBatchOp

use of com.alibaba.alink.operator.batch.evaluation.EvalMultiClassBatchOp in project Alink by alibaba.

the class Chap12 method c_6.

static void c_6() throws Exception {
    AkSourceBatchOp train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TRAIN_FILE);
    AkSourceBatchOp test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TEST_FILE);
    new MultilayerPerceptronClassifier().setLayers(new int[] { 4, 12, 3 }).setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("MultilayerPerceptronClassifier [4, 12, 3]"));
    new MultilayerPerceptronClassifier().setLayers(new int[] { 4, 3 }).setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("MultilayerPerceptronClassifier [4, 3]"));
    BatchOperator.execute();
}

Example 3 with EvalMultiClassBatchOp

use of com.alibaba.alink.operator.batch.evaluation.EvalMultiClassBatchOp in project Alink by alibaba.

the class Chap13 method c_6.

static void c_6() throws Exception {
    BatchOperator.setParallelism(4);
    AkSourceBatchOp train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TRAIN_FILE);
    AkSourceBatchOp test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TEST_FILE);
    new KnnClassifier().setK(3).setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("KnnClassifier - 3 - EUCLIDEAN"));
    BatchOperator.execute();
    new KnnClassifier().setDistanceType(DistanceType.COSINE).setK(3).setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("KnnClassifier - 3 - COSINE"));
    BatchOperator.execute();
    new KnnClassifier().setK(7).setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("KnnClassifier - 7 - EUCLIDEAN"));
    BatchOperator.execute();
}

Example 4 with EvalMultiClassBatchOp

use of com.alibaba.alink.operator.batch.evaluation.EvalMultiClassBatchOp in project Alink by alibaba.

the class Chap13 method c_4.

static void c_4() throws Exception {
    BatchOperator.setParallelism(4);
    AkSourceBatchOp train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TRAIN_FILE);
    AkSourceBatchOp test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TEST_FILE);
    new MultilayerPerceptronClassifier().setLayers(new int[] { 784, 10 }).setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("MultilayerPerceptronClassifier {784, 10}"));
    BatchOperator.execute();
    new MultilayerPerceptronClassifier().setLayers(new int[] { 784, 256, 128, 10 }).setVectorCol(VECTOR_COL_NAME).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalMultiClassBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("MultilayerPerceptronClassifier {784, 256, 128, 10}"));
    BatchOperator.execute();
}

Example 5 with EvalMultiClassBatchOp

use of com.alibaba.alink.operator.batch.evaluation.EvalMultiClassBatchOp 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();
}