我想对我的数据执行10倍交叉验证,并使用了weka java程序。但是,我遇到了异常问题。
以下是例外:
---Registering Weka Editors---
Trying to add database driver (JDBC): jdbc.idbDriver - Error, not in CLASSPATH?
Exception in thread "main" java.lang.IllegalArgumentException: No suitable converter found for ''!
at weka.core.converters.ConverterUtils$DataSource.<init>(ConverterUtils.java:137)
at weka.core.converters.ConverterUtils$DataSource.read(ConverterUtils.java:441)
at crossvalidationmultipleruns.CrossValidationMultipleRuns.main(CrossValidationMultipleRuns.java:45)
C:\Users\TomXavier\AppData\Local\NetBeans\Cache\8.1\executor-snippets\run.xml:53: Java returned: 1
BUILD FAILED (total time: 1 second)
这是我使用的程序:
import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;
import weka.core.Utils;
import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import java.util.Random;
/**
* Performs a single run of cross-validation.
*
* Command-line parameters:
* <ul>
* <li>-t filename - the dataset to use</li>
* <li>-x int - the number of folds to use</li>
* <li>-s int - the seed for the random number generator</li>
* <li>-c int - the class index, "first" and "last" are accepted as well;
* "last" is used by default</li>
* <li>-W classifier - classname and options, enclosed by double quotes;
* the classifier to cross-validate</li>
* </ul>
*
* Example command-line:
* <pre>
* java CrossValidationSingleRun -t anneal.arff -c last -x 10 -s 1 -W "weka.classifiers.trees.J48 -C 0.25"
* </pre>
*
* @author FracPete (fracpete at waikato dot ac dot nz)
*/
public class CrossValidationSingleRun {
/**
* Performs the cross-validation. See Javadoc of class for information
* on command-line parameters.
*
* @param args the command-line parameters
* @throws Excecption if something goes wrong
*/
public static void main(String[] args) throws Exception {
// loads data and set class index
Instances data = DataSource.read(Utils.getOption("C:/Users/TomXavier/Documents/MATLAB/total_data.arff", args));
String clsIndex = Utils.getOption("first", args);
if (clsIndex.length() == 0)
clsIndex = "last";
if (clsIndex.equals("first"))
data.setClassIndex(0);
else if (clsIndex.equals("last"))
data.setClassIndex(data.numAttributes() - 1);
else
data.setClassIndex(Integer.parseInt(clsIndex) - 1);
// classifier
String[] tmpOptions;
String classname;
tmpOptions = Utils.splitOptions(Utils.getOption("weka.classifiers.trees.J48", args));
classname = tmpOptions[0];
tmpOptions[0] = "";
Classifier cls = (Classifier) Utils.forName(Classifier.class, classname, tmpOptions);
// other options
int seed = Integer.parseInt(Utils.getOption("1", args));
int folds = Integer.parseInt(Utils.getOption("10", args));
// randomize data
Random rand = new Random(seed);
Instances randData = new Instances(data);
randData.randomize(rand);
if (randData.classAttribute().isNominal())
randData.stratify(folds);
// perform cross-validation
Evaluation eval = new Evaluation(randData);
for (int n = 0; n < folds; n++) {
Instances train = randData.trainCV(folds, n);
Instances test = randData.testCV(folds, n);
// the above code is used by the StratifiedRemoveFolds filter, the
// code below by the Explorer/Experimenter:
// Instances train = randData.trainCV(folds, n, rand);
// build and evaluate classifier
Classifier clsCopy = Classifier.makeCopy(cls);
clsCopy.buildClassifier(train);
eval.evaluateModel(clsCopy, test);
}
// output evaluation
System.out.println();
System.out.println("=== Setup ===");
System.out.println("Classifier: " + cls.getClass().getName() + " " + Utils.joinOptions(cls.getOptions()));
System.out.println("Dataset: " + data.relationName());
System.out.println("Folds: " + folds);
System.out.println("Seed: " + seed);
System.out.println();
System.out.println(eval.toSummaryString("=== " + folds + "-fold Cross-validation ===", false));
}
}
这个问题有解决办法吗?
非常感谢!