DEVELOPMENT... OpenML
Run
20168

Run 20168

Task 34 (Supervised Classification) postoperative-patient-data Uploaded 18-06-2014 by Felicia West
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Flow

weka.MultiBoostAB_RandomTree(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_RandomTree(1)_C3
weka.MultiBoostAB_RandomTree(1)_I20
weka.MultiBoostAB_RandomTree(1)_P100
weka.MultiBoostAB_RandomTree(1)_S1
weka.MultiBoostAB_RandomTree(1)_Wweka.classifiers.trees.RandomTree
weka.RandomTree(1)_K0
weka.RandomTree(1)_M1.0
weka.RandomTree(1)_S1

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
0.4181
Per class
F measure
0.5523
Per class
Kappa
-0.1175
KB relative information score
-0.6041
Mean absolute error
0.2683
Mean prior absolute error
0.2871
Number of instances
90
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5234
Per class
Predictive accuracy
0.5889
Prior entropy
1.0305
Recall
0.5889
Per class
Relative absolute error
0.9347
Root mean prior squared error
0.3755
Root mean squared error
0.5089
Root relative squared error
1.3554
SciMark benchmark
940.0086[562.1143028726297988.6890749395138482.36378704342826913.07564286738091753.799996626104]