Examples with LogisticRegressionPredictBatchOp com.alibaba.alink.operator.batch.classification.LogisticRegressionPredictBatchOp used on opensource projects

Example 1 with LogisticRegressionPredictBatchOp

use of com.alibaba.alink.operator.batch.classification.LogisticRegressionPredictBatchOp in project Alink by alibaba.

the class Chap08 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);
    LogisticRegressionTrainBatchOp lrTrainer = new LogisticRegressionTrainBatchOp().setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME);
    LogisticRegressionPredictBatchOp lrPredictor = new LogisticRegressionPredictBatchOp().setPredictionCol(PREDICTION_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME);
    train_data.link(lrTrainer);
    lrPredictor.linkFrom(lrTrainer, test_data);
    lrTrainer.lazyPrintTrainInfo().lazyPrintModelInfo();
    lrPredictor.lazyPrint(5, "< Prediction >").link(new AkSinkBatchOp().setFilePath(DATA_DIR + LR_PRED_FILE).setOverwriteSink(true));
    BatchOperator.execute();
}

Example 2 with LogisticRegressionPredictBatchOp

use of com.alibaba.alink.operator.batch.classification.LogisticRegressionPredictBatchOp in project Alink by alibaba.

the class Chap10 method c_1.

static void c_1() throws Exception {
    BatchOperator<?> train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TRAIN_FILE).select(CLAUSE_CREATE_FEATURES);
    BatchOperator<?> test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TEST_FILE).select(CLAUSE_CREATE_FEATURES);
    String[] new_features = ArrayUtils.removeElement(train_data.getColNames(), LABEL_COL_NAME);
    train_data.lazyPrint(5, "< new features >");
    LogisticRegressionTrainBatchOp trainer = new LogisticRegressionTrainBatchOp().setFeatureCols(new_features).setLabelCol(LABEL_COL_NAME);
    LogisticRegressionPredictBatchOp predictor = new LogisticRegressionPredictBatchOp().setPredictionCol(PREDICTION_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME);
    train_data.link(trainer);
    predictor.linkFrom(trainer, test_data);
    trainer.lazyPrintTrainInfo().lazyCollectTrainInfo(new Consumer<LinearModelTrainInfo>() {

        @Override
        public void accept(LinearModelTrainInfo linearModelTrainInfo) {
            printImportance(linearModelTrainInfo.getColNames(), linearModelTrainInfo.getImportance());
        }
    });
    predictor.link(new EvalBinaryClassBatchOp().setPositiveLabelValueString("2").setLabelCol(LABEL_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).lazyPrintMetrics());
    BatchOperator.execute();
}

Example 3 with LogisticRegressionPredictBatchOp

use of com.alibaba.alink.operator.batch.classification.LogisticRegressionPredictBatchOp in project Alink by alibaba.

the class Chap10 method c_2.

static void c_2() throws Exception {
    BatchOperator<?> train_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TRAIN_FILE).select(CLAUSE_CREATE_FEATURES);
    BatchOperator<?> test_data = new AkSourceBatchOp().setFilePath(DATA_DIR + TEST_FILE).select(CLAUSE_CREATE_FEATURES);
    String[] new_features = ArrayUtils.removeElement(train_data.getColNames(), LABEL_COL_NAME);
    train_data.lazyPrint(5, "< new features >");
    LogisticRegressionTrainBatchOp trainer = new LogisticRegressionTrainBatchOp().setFeatureCols(new_features).setLabelCol(LABEL_COL_NAME).setL1(0.01);
    LogisticRegressionPredictBatchOp predictor = new LogisticRegressionPredictBatchOp().setPredictionCol(PREDICTION_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME);
    train_data.link(trainer);
    predictor.linkFrom(trainer, test_data);
    trainer.lazyPrintTrainInfo().lazyCollectTrainInfo(new Consumer<LinearModelTrainInfo>() {

        @Override
        public void accept(LinearModelTrainInfo linearModelTrainInfo) {
            printImportance(linearModelTrainInfo.getColNames(), linearModelTrainInfo.getImportance());
        }
    });
    predictor.link(new EvalBinaryClassBatchOp().setPositiveLabelValueString("2").setLabelCol(LABEL_COL_NAME).setPredictionDetailCol(PRED_DETAIL_COL_NAME).lazyPrintMetrics());
    BatchOperator.execute();
}