DEVELOPMENT... OpenML
Run
23643

Run 23643

Task 57 (Supervised Classification) ionosphere Uploaded 26-06-2014 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)_I80
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
0.8758
Per class
F measure
0.8767
Per class
Kappa
0.7276
KB relative information score
248.766
Mean absolute error
0.1327
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
0.8845
Per class
Predictive accuracy
0.8803
Prior entropy
0.9425
Recall
0.8803
Per class
Relative absolute error
0.2883
Root mean prior squared error
0.4797
Root mean squared error
0.3297
Root relative squared error
0.6873
SciMark benchmark
941.0941[544.90492143430411000.4958509626932483.88543266528814912.7575910626911763.4269028321794]