Question

我使用Weka来训练我的数据集，但我不知道我是否得到了一个好的结果。有人能给我一些想法吗？这是我的结果：

=== Stratified cross-validation ===
=== Summary ===

Correctly Classified Instances        2823               97.9188 %
Incorrectly Classified Instances        60                2.0812 %
Kappa statistic                          0     
Mean absolute error                      0.0208
Root mean squared error                  0.1443
Relative absolute error                 50.6234 %
Root relative squared error            101.0568 %
Coverage of cases (0.95 level)          97.9188 %
Mean rel. region size (0.95 level)      50      %
Total Number of Instances             2883     
Ignored Class Unknown Instances                119     

=== Detailed Accuracy By Class ===

                 TP Rate  FP Rate  Precision  Recall   F-Measure  MCC      ROC Area  PRC Area  Class
                 0.000    0.000    0.000      0.000    0.000      0.000    0.500     0.020     0
                 1.000    1.000    0.979      1.000    0.989      0.000    0.500     0.940     1
Weighted Avg.    0.979    0.979    0.959      0.979    0.969      0.000    0.500     0.921     

=== Confusion Matrix ===

    a    b   <-- classified as
    0   60 |    a = 0
    0 2823 |    b = 1

Answer 1

使用了2个类，用b类标记所有实例正确分类，因此正确分类实例速率= 2823 /（2823 + 60）= 97.9188％，类1 TP值为1，但从未使用正确分类的类实例进行标记所以错误分类的实例率= 60 /（2823 + 60）= 2.0812％且0级TP值为0

如何知道我是否获得了良好的Weka结果

1 个答案: