Examples with XGModelComposition org.apache.ignite.ml.xgboost.XGModelComposition used on opensource projects

Example 1 with XGModelComposition

use of org.apache.ignite.ml.xgboost.XGModelComposition in project ignite by apache.

the class XGModelVisitor method visitXgModel.

/**
 * {@inheritDoc}
 */
@Override
public XGModelComposition visitXgModel(XGBoostModelParser.XgModelContext ctx) {
    List<DecisionTreeNode> trees = new ArrayList<>();
    Set<String> featureNames = new HashSet<>();
    for (XGBoostModelParser.XgTreeContext treeCtx : ctx.xgTree()) featureNames.addAll(treeDictionaryVisitor.visitXgTree(treeCtx));
    Map<String, Integer> dict = buildDictionary(featureNames);
    XGTreeVisitor treeVisitor = new XGTreeVisitor(dict);
    for (XGBoostModelParser.XgTreeContext treeCtx : ctx.xgTree()) {
        DecisionTreeNode treeNode = treeVisitor.visitXgTree(treeCtx);
        trees.add(treeNode);
    }
    return new XGModelComposition(dict, trees);
}

Example 2 with XGModelComposition

use of org.apache.ignite.ml.xgboost.XGModelComposition in project ignite by apache.

the class XGBoostModelParserTest method testParseAndPredict.

/**
 * End-to-end test for {@code parse()} and {@code predict()} methods.
 */
@Test
public void testParseAndPredict() {
    URL url = XGBoostModelParserTest.class.getClassLoader().getResource(TEST_MODEL_RESOURCE);
    if (url == null)
        throw new IllegalStateException("File not found [resource_name=" + TEST_MODEL_RESOURCE + "]");
    ModelReader reader = new FileSystemModelReader(url.getPath());
    try (XGModelComposition mdl = mdlBuilder.build(reader, parser);
        Scanner testDataScanner = new Scanner(XGBoostModelParserTest.class.getClassLoader().getResourceAsStream("datasets/agaricus-test-data.txt"));
        Scanner testExpResultsScanner = new Scanner(XGBoostModelParserTest.class.getClassLoader().getResourceAsStream("datasets/agaricus-test-expected-results.txt"))) {
        while (testDataScanner.hasNextLine()) {
            assertTrue(testExpResultsScanner.hasNextLine());
            String testDataStr = testDataScanner.nextLine();
            String testExpResultsStr = testExpResultsScanner.nextLine();
            HashMap<String, Double> testObj = new HashMap<>();
            for (String keyValueString : testDataStr.split(" ")) {
                String[] keyVal = keyValueString.split(":");
                if (keyVal.length == 2)
                    testObj.put("f" + keyVal[0], Double.parseDouble(keyVal[1]));
            }
            double prediction = mdl.predict(VectorUtils.of(testObj));
            double expPrediction = Double.parseDouble(testExpResultsStr);
            assertEquals(expPrediction, prediction, 1e-6);
        }
    }
}