DEVELOPMENT... OpenML
Run
142344

Run 142344

Task 3921 (Supervised Classification) jEdit_4.0_4.2 Uploaded 01-01-2015 by Felicia West
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Flow

weka.AdaBoostM1_SMO_PolyKernel(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_SMO_PolyKernel(2)_I80
weka.AdaBoostM1_SMO_PolyKernel(2)_P100
weka.AdaBoostM1_SMO_PolyKernel(2)_S1
weka.AdaBoostM1_SMO_PolyKernel(2)_Wweka.classifiers.functions.SMO
weka.SMO_PolyKernel(7)_C1.0
weka.SMO_PolyKernel(7)_L0.001
weka.SMO_PolyKernel(7)_N0
weka.SMO_PolyKernel(7)_P1.0E-12
weka.SMO_PolyKernel(7)_V-1
weka.SMO_PolyKernel(7)_W1

Result files

xml
Description

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

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

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

21 Evaluation measures

Area under ROC curve
0.7696
Per class
Build CPU time
0.1201
Build memory
1035912835.854
F measure
0.7001
Per class
Kappa
0.4002
KB relative information score
72.3422
Mean absolute error
0.3795
Mean prior absolute error
0.4998
Number of instances
274
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7013
Per class
Predictive accuracy
0.7007
Prior entropy
0.9997
Recall
0.7007
Per class
Relative absolute error
0.7593
Root mean prior squared error
0.4999
Root mean squared error
0.4462
Root relative squared error
0.8926
SciMark benchmark
882.4531