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Decision Tree: C4.5
Data: iris (範例)

C4.5 範例 Output 說明


C4.5 [release 8] decision tree generator Thu Jan 15 03:28:47 2009
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Options:
File stem
Trees evaluated on unseen cases

Read 120 cases (4 attributes) from http://netstat.stat.tku.edu.tw/tmp/dm/1231961326_kx2mg.train.data

============================================= Decision Tree: =============================================

PetalWidth <= 0.6 : setosa (43.0)
PetalWidth > 0.6 :
| PetalLength > 4.9 : virginica (36.0)
| PetalLength <= 4.9 :
| | PetalWidth <= 1.6 : versicolor (36.0)
| | PetalWidth > 1.6 : virginica (5.0/1.0)


--------------------------------------------- Tree saved




Evaluation on training data (120 items):

Before Pruning After Pruning
---------------- ---------------------------
Size Errors Size Errors Estimate

7 1( 0.8%) 7 1( 0.8%) ( 5.3%) <<

Evaluation on test data (30 items):

Before Pruning After Pruning
---------------- ---------------------------
Size Errors Size Errors Estimate

7 2( 6.7%) 7 2( 6.7%) ( 5.3%) <<


============================================= Confusion Matrix ============================================= (a) (b) (c) <-classified as
---- ---- ----
7 0 0 (a): class setosa
0 11 2 (b): class versicolor
0 0 10 (c): class virginica



 

Correct Classification Rate: 0.93