DEVELOPMENT... OpenML
Run
20190

Run 20190

Task 27 (Supervised Classification) colic Uploaded 18-06-2014 by Felicia West
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Flow

weka.MultiBoostAB_BFTree(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.BFTree(1)_Ctrue
weka.BFTree(1)_M2
weka.BFTree(1)_N5
weka.BFTree(1)_PPOSTPRUNED
weka.BFTree(1)_S1
weka.MultiBoostAB_BFTree(1)_C3
weka.MultiBoostAB_BFTree(1)_I40
weka.MultiBoostAB_BFTree(1)_P100
weka.MultiBoostAB_BFTree(1)_S1
weka.MultiBoostAB_BFTree(1)_Wweka.classifiers.trees.BFTree

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.8686
Per class
F measure
0.8356
Per class
Kappa
0.6447
KB relative information score
235.3003
Mean absolute error
0.1631
Mean prior absolute error
0.4662
Number of instances
368
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8355
Per class
Predictive accuracy
0.837
Prior entropy
0.9509
Recall
0.837
Per class
Relative absolute error
0.3499
Root mean prior squared error
0.4827
Root mean squared error
0.3948
Root relative squared error
0.8178
SciMark benchmark
903.7939[560.12864292244511009.4054313942349480.4213690634573905.5060508708661563.5079546575598]