use of org.apache.ignite.ml.preprocessing.binarization.BinarizationTrainer in project ignite by apache.
the class BinarizationExample method main.
/**
* Run example.
*/
public static void main(String[] args) throws Exception {
try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
System.out.println(">>> Binarization example started.");
IgniteCache<Integer, Vector> data = null;
try {
data = createCache(ignite);
Vectorizer<Integer, Vector, Integer, Double> vectorizer = new DummyVectorizer<>(1);
// Defines second preprocessor that binarizes features.
Preprocessor<Integer, Vector> preprocessor = new BinarizationTrainer<Integer, Vector>().withThreshold(40).fit(ignite, data, vectorizer);
// Creates a cache based simple dataset containing features and providing standard dataset API.
try (SimpleDataset<?> dataset = DatasetFactory.createSimpleDataset(ignite, data, preprocessor)) {
new DatasetHelper(dataset).describe();
}
System.out.println(">>> Binarization example completed.");
} finally {
data.destroy();
}
} finally {
System.out.flush();
}
}
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