myeclipse下java调用weka

代码示例

package test;import java.io.File;import weka.classifiers.Classifier;import weka.classifiers.trees.J48;import weka.core.Instances;import weka.core.converters.ArffLoader;public class WekaTest {public static void main(String[] args) throws Exception {Classifier m_classifier = new J48();// 训练语料文件File inputFile = new File("D:/Program Files/Weka-3-6/data/cpu.with.vendor.arff");ArffLoader atf = new ArffLoader();atf.setFile(inputFile);// 读入训练文件Instances instancesTrain = atf.getDataSet();instancesTrain.setClassIndex(0);// 训练m_classifier.buildClassifier(instancesTrain);// 测试语料文件inputFile = new File("D:/Program Files/Weka-3-6/data/cpu.with.vendor.arff");atf.setFile(inputFile);// 读入测试文件Instances instancesTest = atf.getDataSet();// 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(0);// 测试语料实例数double sum = instancesTest.numInstances();double right = 0.0f;// 测试分类结果for (int i = 0; i < sum; i++) {// 如果预测值和答案值相等（测试语料中的分类列提供的须为正确答案，结果才有意义）if (m_classifier.classifyInstance(instancesTest.instance(i)) == instancesTest.instance(i).classValue()) {// 正确值加1right++;}}System.out.println("J48 classification precision:" + (right / sum));}}

操作步骤

1. 新建一个java project，创建类WekaTest
2. 引入weka.jar包（weka安装目录D:\Program Files\Weka-3-6\weka.jar）

问题

调用过程顺利，但是结果与在weka中得出的结果不同，贴出图，求明白人指点

程序运行结果：

J48 classification precision:0.8373205741626795

WEKA运行结果:

=== Run information ===Scheme:weka.classifiers.trees.J48 -C 0.25 -M 2Relation:     bank-data-weka.filters.unsupervised.attribute.Remove-R1Instances:    600Attributes:   11              age              sex              region              income              married              children              car              save_act              current_act              mortgage              pepTest mode:evaluate on training data=== Classifier model (full training set) ===J48 pruned tree------------------children <= 1|   children <= 0|   |   married = NO|   |   |   mortgage = NO: YES (48.0/3.0)|   |   |   mortgage = YES|   |   |   |   save_act = NO: YES (12.0)|   |   |   |   save_act = YES: NO (23.0)|   |   married = YES|   |   |   save_act = NO|   |   |   |   mortgage = NO|   |   |   |   |   income <= 21506.2|   |   |   |   |   |   age <= 41: NO (11.0/1.0)|   |   |   |   |   |   age > 41: YES (5.0/1.0)|   |   |   |   |   income > 21506.2: NO (20.0)|   |   |   |   mortgage = YES: YES (25.0/3.0)|   |   |   save_act = YES: NO (119.0/12.0)|   children > 0|   |   income <= 15538.8|   |   |   age <= 41: NO (22.0/2.0)|   |   |   age > 41: YES (2.0)|   |   income > 15538.8: YES (111.0/5.0)children > 1|   income <= 30404.3: NO (124.0/12.0)|   income > 30404.3|   |   children <= 2: YES (51.0/5.0)|   |   children > 2|   |   |   income <= 44288.3: NO (19.0/2.0)|   |   |   income > 44288.3: YES (8.0)Number of Leaves  : 15Size of the tree : 29Time taken to build model: 0.01 seconds=== Evaluation on training set ====== Summary ===Correctly Classified Instances         554               92.3333 %Incorrectly Classified Instances        46                7.6667 %Kappa statistic                          0.845 K&B Relative Info Score              45010.1705 %K&B Information Score                  447.6762 bits      0.7461 bits/instanceClass complexity | order 0             596.7451 bits      0.9946 bits/instanceClass complexity | scheme              222.7757 bits      0.3713 bits/instanceComplexity improvement     (Sf)        373.9693 bits      0.6233 bits/instanceMean absolute error                      0.1389Root mean squared error                  0.2636Relative absolute error                 27.9979 %Root relative squared error             52.9137 %Total Number of Instances              600     === Detailed Accuracy By Class ===               TP Rate   FP Rate   Precision   Recall  F-Measure   ROC Area  Class                 0.894     0.052      0.935     0.894     0.914      0.936    YES                 0.948     0.106      0.914     0.948     0.931      0.936    NOWeighted Avg.    0.923     0.081      0.924     0.923     0.923      0.936=== Confusion Matrix ===   a   b   <-- classified as 245  29 |   a = YES  17 309 |   b = NO

 

quote：http://blog.csdn.net/felomeng/article/details/4688257#comments