我正在尝试从心脏病学-weka.arff了解WEKA J48决策树。
我已按以下方式运行输出,
Test mode:10-fold cross-validation
=== Classifier model (full training set) ===
J48 pruned tree
------------------
thal = Rev
| chest-pain-type = Asymptomatic: Sick (79.0/7.0)
| chest-pain-type = AbnormalAngina
| | #colored-vessels = 0
| | | peak <= 0.1: Healthy (4.0)
| | | peak > 0.1: Sick (3.0/1.0)
| | #colored-vessels = 1: Sick (2.0)
| | #colored-vessels = 2: Healthy (0.0)
| | #colored-vessels = 3: Healthy (0.0)
| chest-pain-type = Angina
| | cholesterol <= 229: Healthy (3.0)
| | cholesterol > 229
| | | age <= 48: Sick (2.0)
| | | age > 48: Healthy (3.0/1.0)
| chest-pain-type = NoTang
| | slope = Flat
| | | #colored-vessels = 0
| | | | blood-pressure <= 122: Healthy (3.0)
| | | | blood-pressure > 122: Sick (3.0)
| | | #colored-vessels = 1: Sick (5.0)
| | | #colored-vessels = 2: Sick (0.0)
| | | #colored-vessels = 3: Sick (3.0/1.0)
| | slope = Up: Healthy (7.0/1.0)
| | slope = Down: Healthy (1.0)
thal = Normal
| #colored-vessels = 0: Healthy (118.0/12.0)
| #colored-vessels = 1
| | sex = Male
| | | chest-pain-type = Asymptomatic: Sick (9.0)
| | | chest-pain-type = AbnormalAngina: Sick (2.0/1.0)
| | | chest-pain-type = Angina: Healthy (3.0/1.0)
| | | chest-pain-type = NoTang: Healthy (2.0)
| | sex = Female: Healthy (13.0/1.0)
| #colored-vessels = 2
| | angina = TRUE: Sick (3.0)
| | angina = FALSE
| | | age <= 62
| | | | age <= 53: Healthy (2.0)
| | | | age > 53: Sick (4.0)
| | | age > 62: Healthy (5.0)
| #colored-vessels = 3: Sick (6.0/1.0)
thal = Fix
| #colored-vessels = 0
| | angina = TRUE: Sick (3.0/1.0)
| | angina = FALSE: Healthy (5.0)
| #colored-vessels = 1: Sick (4.0)
| #colored-vessels = 2: Sick (4.0)
| #colored-vessels = 3: Sick (2.0)
Number of Leaves : 32
Size of the tree : 49
Time taken to build model: 0.03 seconds
=== Stratified cross-validation ===
=== Summary ===
Correctly Classified Instances 222 73.2673 %
Incorrectly Classified Instances 81 26.7327 %
Kappa statistic 0.4601
Mean absolute error 0.3067
Root mean squared error 0.4661
Relative absolute error 61.8185 %
Root relative squared error 93.5807 %
Total Number of Instances 303
=== Detailed Accuracy By Class ===
TP Rate FP Rate Precision Recall F-Measure ROC Area Class
0.696 0.236 0.711 0.696 0.703 0.756 Sick
0.764 0.304 0.75 0.764 0.757 0.756 Healthy
Weighted Avg. 0.733 0.273 0.732 0.733 0.732 0.756
=== Confusion Matrix ===
a b <-- classified as
96 42 | a = Sick
39 126 | b = Healthy
问题是
到目前为止,我只能解释关于正确分类的混淆矩阵。任何帮助将不胜感激。
答案 0 :(得分:3)
最顶层的节点是&#34; thal&#34;,它有三个不同的级别。
您可以使用&#34; visualize tree&#34;在weka中将树绘制为图表。 。在模型结果上,左键单击或右键单击&#34; J48 - 20151206 10:33&#34; (或类似的东西)。亲自尝试或搜索我提供截图的答案(如何执行此操作)
你可以通过&#34;修剪&#34;来约束树。它在J48配置对话框中为n级。