DEVELOPMENT... OpenML
Run
15422

Run 15422

Task 57 (Supervised Classification) ionosphere Uploaded 04-06-2014 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
0.8935
Per class
F measure
0.8736
Per class
Kappa
0.7206
KB relative information score
248.4158
Mean absolute error
0.133
Mean prior absolute error
0.4604
Number of instances
351
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.882
Per class
Predictive accuracy
0.8775
Prior entropy
0.9425
Recall
0.8775
Per class
Relative absolute error
0.2887
Root mean prior squared error
0.4797
Root mean squared error
0.3266
Root relative squared error
0.6809
SciMark benchmark
938.8164[556.19919821977941009.4054313942349474.267552947349907.70082742804311746.5088487702178]

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