DEVELOPMENT... OpenML
Run
140720

Run 140720

Task 1819 (Supervised Classification) vote Uploaded 31-12-2014 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)_I20
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
0.9676
Per class
Build CPU time
0.1473
Build memory
1285338757.5172
F measure
0.9431
Per class
Kappa
0.8804
KB relative information score
1907.056
Mean absolute error
0.0569
Mean prior absolute error
0.4742
Number of instances
2175
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9435
Per class
Predictive accuracy
0.943
Prior entropy
0.9627
Recall
0.943
Per class
Relative absolute error
0.12
Root mean prior squared error
0.4869
Root mean squared error
0.2331
Root relative squared error
0.4787
SciMark benchmark
941.7891