为啥在 Weka 中使用 libsvm 时会出现“NoClassDefFoundError:libsvm/svm_print_interface”错误?
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【中文标题】为啥在 Weka 中使用 libsvm 时会出现“NoClassDefFoundError:libsvm/svm_print_interface”错误?【英文标题】:Why does "NoClassDefFoundError:libsvm/svm_print_interface" error occur when using libsvm in Weka?为什么在 Weka 中使用 libsvm 时会出现“NoClassDefFoundError:libsvm/svm_print_interface”错误? 【发布时间】:2018-11-02 09:35:41 【问题描述】:我的任务是在 weka 中使用 libsvm 对 Iris 数据集进行分类。首先,我在 weka explorer 中运行它并得到理想的结果。
然后我在eclipse中编码,希望得到与weka explorer下面显示的相同的结果。这是我的代码(你可以忽略除main函数之外的任何代码)。
package weka;
import java.io.BufferedReader;
import java.io.FileReader;
import java.util.Vector;
import weka.classifiers.AbstractClassifier;
import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.core.Instances;
import weka.core.OptionHandler;
import weka.core.Utils;
import weka.filters.Filter;
import weka.classifiers.functions.LibSVM;
public class ClassifyIriswithLibsvm
/** the classifier used internally */
protected Classifier m_Classifier = null;
/** the filter to use */
protected Filter m_Filter = null;
/** the training file */
protected String m_TrainingFile = null;
/** the training instances */
protected Instances m_Training = null;
/** for evaluating the classifier */
protected Evaluation m_Evaluation = null;
/**
* initializes the demo
*/
public ClassifyIriswithLibsvm ()
super();
/**
* sets the classifier to use
*
* @param name the classname of the classifier
* @param options the options for the classifier
*/
public void setClassifier(String name, String[] options) throws Exception
m_Classifier = AbstractClassifier.forName(name, options);
/**
* sets the filter to use
*
* @param name the classname of the filter
*/
public void setFilter(String name) throws Exception
m_Filter = (Filter) Class.forName(name).newInstance();
if (m_Filter instanceof OptionHandler)
((OptionHandler) m_Filter).setOptions(options);
/**
* sets the file to use for training
*/
public void setTraining(String name) throws Exception
m_TrainingFile = name;
m_Training = new Instances(new BufferedReader(
new FileReader(m_TrainingFile)));
m_Training.setClassIndex(m_Training.numAttributes() - 1);
/**
* runs 10fold CV over the training file
*/
public void execute() throws Exception
// run filter
m_Filter.setInputFormat(m_Training);
Instances filtered = Filter.useFilter(m_Training, m_Filter);
// train classifier on complete file for tree
m_Classifier.buildClassifier(filtered);
// 10fold CV with seed=1
m_Evaluation = new Evaluation(filtered);
m_Evaluation.crossValidateModel(m_Classifier, filtered, 10,
m_Training.getRandomNumberGenerator(1));
/**
* outputs some data about the classifier
*/
@Override
public String toString()
StringBuffer result;
result = new StringBuffer();
result.append("Weka - Demo\n===========\n\n");
result.append("Classifier...: " + Utils.toCommandLine(m_Classifier) + "\n");
if (m_Filter instanceof OptionHandler)
result.append("Filter.......: " + m_Filter.getClass().getName() + " "
+ Utils.joinOptions(((OptionHandler) m_Filter).getOptions()) + "\n");
else
result.append("Filter.......: " + m_Filter.getClass().getName() + "\n");
result.append("Training file: " + m_TrainingFile + "\n");
result.append("\n");
result.append(m_Classifier.toString() + "\n");
result.append(m_Evaluation.toSummaryString() + "\n");
try
result.append(m_Evaluation.toMatrixString() + "\n");
catch (Exception e)
e.printStackTrace();
try
result.append(m_Evaluation.toClassDetailsString() + "\n");
catch (Exception e)
e.printStackTrace();
return result.toString();
public static void main(String[] args) throws Exception
String classifier = "weka.classifiers.functions.LibSVM" ;
String options = ( "-S 0 -K 0 -D 3 -G 0.0 -R 0.0 -N 0.5 -M 40.0 -C 1.0 -E 0.001 -P 0.1" );
String[] classifierOptions = options.split( " " );
String filter = "weka.filters.unsupervised.instance.Randomize ";
String dataset = "D:\\SoftWare\\weka3.8.2\\Weka-3-8\\data\\iris.arff";
// run
ClassifyIriswithLibsvm demo = new ClassifyIriswithLibsvm();
demo.setClassifier(classifier,
classifierOptions);
demo.setFilter(filter);
demo.setTraining(dataset);
demo.execute();
System.out.println(demo.toString());
但是错误打印出来是这样的
`Exception in thread "main" java.lang.NoClassDefFoundError: libsvm/svm_print_interface
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Unknown Source)
at weka.core.WekaPackageClassLoaderManager.forName(WekaPackageClassLoaderManager.java:198)
at weka.core.WekaPackageClassLoaderManager.forName(WekaPackageClassLoaderManager.java:178)
at weka.core.WekaPackageClassLoaderManager.objectForName(WekaPackageClassLoaderManager.java:162)
at weka.Run.findSchemeMatch(Run.java:90)
at weka.core.ResourceUtils.forName(ResourceUtils.java:76)
at weka.core.Utils.forName(Utils.java:1045)
at weka.classifiers.AbstractClassifier.forName(AbstractClassifier.java:91)
at weka.ClassifyIriswithLibsvm.setClassifier(ClassifyIriswithLibsvm.java:46)
at weka.ClassifyIriswithLibsvm.main(ClassifyIriswithLibsvm.java:221)
Caused by: java.lang.ClassNotFoundException: libsvm.svm_print_interface
at java.net.URLClassLoader.findClass(Unknown Source)
at java.lang.ClassLoader.loadClass(Unknown Source)
at sun.misc.Launcher$AppClassLoader.loadClass(Unknown Source)
at java.lang.ClassLoader.loadClass(Unknown Source)
... 11 more
`
我不知道为什么会出错。我是 libsvm 和 weka 的新手。如何在 weka 中成功运行使用 libsvm 的 classiyier 程序?
【问题讨论】:
【参考方案1】:您需要确保 libsvm.jar
在您的类路径中可用(在 Eclipse 中)。
您可以在 *** 上检查 this answer 以获取所有必要的依赖项,它们是 libsvm.jar
、wlsvm.jar
和(当然)weka.jar
。
【讨论】:
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