java weka 随机森林怎么使用

以下是使用Java Weka库中的随机森林进行特征选择的示例代码：

import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;
import weka.classifiers.meta.AttributeSelectedClassifier;
import weka.classifiers.trees.RandomForest;
import weka.filters.supervised.attribute.AttributeSelection;

public class RandomForestFeatureSelection {
    public static void main(String[] args) throws Exception {
        // 加载训练数据
        DataSource source = new DataSource("path_to_training_data.arff");
        Instances data = source.getDataSet();
        if (data.classIndex() == -1) {
            data.setClassIndex(data.numAttributes() - 1);
        }

        // 随机森林分类器
        RandomForest rf = new RandomForest();
        rf.setNumTrees(100);

        // 特征选择
        AttributeSelectedClassifier classifier = new AttributeSelectedClassifier();
        classifier.setClassifier(rf);
        AttributeSelection filter = new AttributeSelection();
        classifier.setFilter(filter);

        // 加载测试数据
        DataSource sourceTest = new DataSource("path_to_test_data.arff");
        Instances testData = sourceTest.getDataSet();
        if (testData.classIndex() == -1) {
            testData.setClassIndex(testData.numAttributes() - 1);
        }

        // 训练和测试
        classifier.buildClassifier(data);
        for (int i = 0; i < testData.numInstances(); i++) {
            double pred = classifier.classifyInstance(testData.instance(i));
            System.out.println("预测结果：" + pred);
        }
    }
}