Examples with AkSourceBatchOp com.alibaba.alink.operator.batch.source.AkSourceBatchOp used on opensource projects

Example 11 with AkSourceBatchOp

use of com.alibaba.alink.operator.batch.source.AkSourceBatchOp 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 12 with AkSourceBatchOp

use of com.alibaba.alink.operator.batch.source.AkSourceBatchOp 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 13 with AkSourceBatchOp

use of com.alibaba.alink.operator.batch.source.AkSourceBatchOp 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 14 with AkSourceBatchOp

use of com.alibaba.alink.operator.batch.source.AkSourceBatchOp in project Alink by alibaba.

the class Chap13 method c_1.

static void c_1() throws Exception {
    if (!new File(DATA_DIR + SPARSE_TRAIN_FILE).exists()) {
        new MnistGzFileSourceBatchOp(DATA_DIR + "train-images-idx3-ubyte.gz", DATA_DIR + "train-labels-idx1-ubyte.gz", true).link(new AkSinkBatchOp().setFilePath(DATA_DIR + SPARSE_TRAIN_FILE));
        BatchOperator.execute();
        new MnistGzFileSourceBatchOp(DATA_DIR + "t10k-images-idx3-ubyte.gz", DATA_DIR + "t10k-labels-idx1-ubyte.gz", true).link(new AkSinkBatchOp().setFilePath(DATA_DIR + SPARSE_TEST_FILE));
        BatchOperator.execute();
        new MnistGzFileSourceBatchOp(DATA_DIR + "train-images-idx3-ubyte.gz", DATA_DIR + "train-labels-idx1-ubyte.gz", false).link(new AkSinkBatchOp().setFilePath(DATA_DIR + DENSE_TRAIN_FILE));
        BatchOperator.execute();
        new MnistGzFileSourceBatchOp(DATA_DIR + "t10k-images-idx3-ubyte.gz", DATA_DIR + "t10k-labels-idx1-ubyte.gz", false).link(new AkSinkBatchOp().setFilePath(DATA_DIR + DENSE_TEST_FILE));
        BatchOperator.execute();
    }
    new AkSourceBatchOp().setFilePath(DATA_DIR + DENSE_TRAIN_FILE).lazyPrint(1, "MNIST data").link(new VectorSummarizerBatchOp().setSelectedCol(VECTOR_COL_NAME).lazyPrintVectorSummary());
    new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TRAIN_FILE).lazyPrint(1, "MNIST data").link(new VectorSummarizerBatchOp().setSelectedCol(VECTOR_COL_NAME).lazyPrintVectorSummary());
    new AkSourceBatchOp().setFilePath(DATA_DIR + SPARSE_TRAIN_FILE).lazyPrintStatistics().groupBy(LABEL_COL_NAME, LABEL_COL_NAME + ", COUNT(*) AS cnt").orderBy("cnt", 100).lazyPrint(-1);
    BatchOperator.execute();
}

Example 15 with AkSourceBatchOp

use of com.alibaba.alink.operator.batch.source.AkSourceBatchOp 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();
}