public static void trainModel(Instances dataTrain, Instances dataTest) {
try {
LibLINEAR classifier = new LibLINEAR();
classifier.setBias(10);
classifier.buildClassifier(dataTrain);
Evaluation eval = new Evaluation(dataTrain);
eval.evaluateModel(classifier, dataTest);
System.out.println(eval.toSummaryString("\nResults\n======\n", false));
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
public double getLiblinear(String path, String train, String test) {
// 本次精确度
double accuracy = 0.0;
try {
LibLINEAR c1 = new LibLINEAR();
// * String[] options=weka.core.Utils.splitOptions(
// * "-S 1 -C 1.0 -E 0.001 -B 0"); c1.setOptions(options);
ArffLoader atf = new ArffLoader();
File TraininputFile = new File(train);
atf.setFile(TraininputFile); // 训练语料文件
Instances instancesTrain = atf.getDataSet(); // 读入训练文件
instancesTrain.setClassIndex(instancesTrain.numAttributes() - 1);
File TestinputFile = new File(test);
atf.setFile(TestinputFile); // 测试语料文件
Instances instancesTest = atf.getDataSet(); // 读入测试文件
// 设置分类属性所在行号（第一行为0号），instancesTest.numAttributes()可以取得属性总数
instancesTest.setClassIndex(instancesTest.numAttributes() - 1);
c1.buildClassifier(instancesTrain); // 训练
Evaluation eval = new Evaluation(instancesTrain);
eval.evaluateModel(c1, instancesTest);
// eval.crossValidateModel(c1, instancesTrain, 10, new
// Random(1));
File newfile = new File(path + "OutLiblinear_temp" + ".txt");
BufferedWriter bufferedWriter =
new BufferedWriter(new OutputStreamWriter(new FileOutputStream(newfile), "utf-8"));
bufferedWriter.write(eval.toSummaryString() + "\r\n");
bufferedWriter.write(eval.toClassDetailsString() + "\r\n");
bufferedWriter.write(eval.toMatrixString() + "\r\n");
bufferedWriter.flush();
bufferedWriter.close();
BufferedReader bufferedReader = new BufferedReader(new FileReader(newfile));
String[] splitLineString = new String[5];
while (bufferedReader.ready()) {
bufferedReader.readLine();
String lineString = bufferedReader.readLine();
splitLineString = lineString.split(" ");
System.out.println(splitLineString[4]);
break;
}
bufferedReader.close();
// 求分类准确度
String tempLine;
BufferedReader tempBF = new BufferedReader(new FileReader(newfile));
while (tempBF.ready()) {
tempLine = tempBF.readLine();
if (tempLine.contains("Correctly Classified Instances")) {
tempLine = tempLine.substring(tempLine.lastIndexOf(".") - 2, tempLine.lastIndexOf(" "));
accuracy = Double.parseDouble(tempLine);
break;
}
}
tempBF.close();
} catch (Exception e) {
System.out.println("Can't run linlinear of weka.");
}
return accuracy;
}
