DEVELOPMENT... OpenML
Run
83503

Run 83503

Task 27 (Supervised Classification) colic Uploaded 02-12-2014 by Felicia West
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Flow

weka.Bagging_SMO_PolyKernel(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_SMO_PolyKernel(2)_I160
weka.Bagging_SMO_PolyKernel(2)_P100
weka.Bagging_SMO_PolyKernel(2)_S1
weka.Bagging_SMO_PolyKernel(2)_Wweka.classifiers.functions.SMO
weka.Bagging_SMO_PolyKernel(2)_num-slots1
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
0.8734
Per class
Build CPU time
8.8701
Build memory
3255278717.4783
F measure
0.8172
Per class
Kappa
0.6063
KB relative information score
210.2594
Mean absolute error
0.1997
Mean prior absolute error
0.4662
Number of instances
368
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8168
Per class
Predictive accuracy
0.8179
Prior entropy
0.9509
Recall
0.8179
Per class
Relative absolute error
0.4284
Root mean prior squared error
0.4827
Root mean squared error
0.3669
Root relative squared error
0.7601
SciMark benchmark
949.2096