DEVELOPMENT... OpenML
Run
18198

Run 18198

Task 35 (Supervised Classification) dermatology Uploaded 10-06-2014 by Felicia West
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Flow

weka.MultiBoostAB_SMO_PolyKernel(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_SMO_PolyKernel(1)_C3
weka.MultiBoostAB_SMO_PolyKernel(1)_I160
weka.MultiBoostAB_SMO_PolyKernel(1)_P100
weka.MultiBoostAB_SMO_PolyKernel(1)_S1
weka.MultiBoostAB_SMO_PolyKernel(1)_Wweka.classifiers.functions.SMO
weka.SMO_PolyKernel(5)_C1.0
weka.SMO_PolyKernel(5)_L0.001
weka.SMO_PolyKernel(5)_N0
weka.SMO_PolyKernel(5)_P1.0E-12
weka.SMO_PolyKernel(5)_V-1
weka.SMO_PolyKernel(5)_W1

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
0.9835
Per class
F measure
0.9561
Per class
Kappa
0.9453
KB relative information score
148.1758
Mean absolute error
0.2016
Mean prior absolute error
0.2664
Number of instances
366
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9561
Per class
Predictive accuracy
0.9563
Prior entropy
2.4378
Recall
0.9563
Per class
Relative absolute error
0.7565
Root mean prior squared error
0.3649
Root mean squared error
0.2972
Root relative squared error
0.8145
SciMark benchmark
908.0941[543.37713996006451012.0561783624415483.0147548568529874.68802747803971627.3341538266843]

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