DEVELOPMENT... OpenML
Run
142383

Run 142383

Task 38 (Supervised Classification) ecoli Uploaded 02-01-2015 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)_I160
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
0.9559
Per class
Build CPU time
0.4441
Build memory
682398699.2619
F measure
0.8477
Per class
Kappa
0.8009
KB relative information score
206.7121
Mean absolute error
0.0905
Mean prior absolute error
0.1828
Number of instances
336
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8495
Per class
Predictive accuracy
0.8571
Prior entropy
2.2353
Recall
0.8571
Per class
Relative absolute error
0.4952
Root mean prior squared error
0.3016
Root mean squared error
0.1782
Root relative squared error
0.5909
SciMark benchmark
940.159