Run
142374

Run 142374

Task 27 (Supervised Classification) colic Uploaded 02-01-2015 by Joaquin Vanschoren
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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
0.8345
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
1.2076
Cross-validation details (10-fold Crossvalidation)
Build memory
702393048.6087
Cross-validation details (10-fold Crossvalidation)
F measure
0.8023
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5775
Cross-validation details (10-fold Crossvalidation)
KB relative information score
188.1361
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2281
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4662
Cross-validation details (10-fold Crossvalidation)
Number of instances
368
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8034
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8016
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9509
Cross-validation details (10-fold Crossvalidation)
Recall
0.8016
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4893
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4827
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4082
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8456
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
940.159