如何在WEKA上使用2个数据集，1个用于训练，1个用于测试，用于情感分析

@relation sentiment_analysis

@attribute text string
@attribute sentiment {positive, negative, neutral}

@data
"This is a great product!", positive
"I hate this service.", negative
"It's okay.", neutral
...

import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;

// 加载训练集
DataSource trainSource = new DataSource("path_to_train.arff");
Instances trainData = trainSource.getDataSet();
trainData.setClassIndex(trainData.numAttributes() - 1);

// 加载测试集
DataSource testSource = new DataSource("path_to_test.arff");
Instances testData = testSource.getDataSet();
testData.setClassIndex(testData.numAttributes() - 1);

import weka.classifiers.Classifier;
import weka.classifiers.bayes.NaiveBayes;

// 创建分类器实例
Classifier classifier = new NaiveBayes();

// 训练模型
classifier.buildClassifier(trainData);

import weka.classifiers.Evaluation;

// 进行预测并评估
Evaluation eval = new Evaluation(trainData);
eval.evaluateModel(classifier, testData);

// 输出评估结果
System.out.println(eval.toSummaryString("\nResults\n======\n", false));