use of com.alibaba.alink.pipeline.regression.DecisionTreeRegressor in project Alink by alibaba.
the class Chap16 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 DecisionTreeRegressor().setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalRegressionBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("DecisionTreeRegressor"));
BatchOperator.execute();
for (int numTrees : new int[] { 2, 4, 8, 16, 32, 64, 128 }) {
new RandomForestRegressor().setNumTrees(numTrees).setFeatureCols(FEATURE_COL_NAMES).setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).fit(train_data).transform(test_data).link(new EvalRegressionBatchOp().setLabelCol(LABEL_COL_NAME).setPredictionCol(PREDICTION_COL_NAME).lazyPrintMetrics("RandomForestRegressor - " + numTrees));
BatchOperator.execute();
}
}
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