=== Run information ===

Scheme: weka.classifiers.rules.DecisionTable -X 1 -S 5

Relation: iris

Instances: 150

Attributes: 5

sepallength

sepalwidth

petallength

petalwidth

class

Test mode: 10-fold cross-validation

=== Classifier model (full training set) ===

Decision Table:

Number of training instances: 150

Number of Rules : 6

Non matches covered by Majority class.

Best first search for feature set,

terminated after 5 non improving subsets.

Evaluation (for feature selection): CV (leave one out)

Feature set: 3,4,5

Time taken to build model: 0.05 seconds

=== Stratified cross-validation ===

=== Summary ===

Correctly Classified Instances 139 92.6667 %

Incorrectly Classified Instances 11 7.3333 %

Kappa statistic 0.89

Mean absolute error 0.0602

Root mean squared error 0.2107

Relative absolute error 13.5405 %

Root relative squared error 44.6992 %

Total Number of Instances 150

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class

1 0 1 1 1 Iris-setosa

0.88 0.05 0.898 0.88 0.889 Iris-versicolor

0.9 0.06 0.882 0.9 0.891 Iris-virginica

=== Confusion Matrix ===

a b c <-- classified as

50 0 0 | a = Iris-setosa

0 44 6 | b = Iris-versicolor

0 5 45 | c = Iris-virginica

这是用WEKA分类分析的结果，老师要求对数据进行说明，可是好多东西不明白哦～

诸如TP rate……请哪位好心人能专业地说明一下以上数据，做个范例,小女子感激不尽……