DEVELOPMENT... OpenML
Run
88706

Run 88706

Task 3895 (Supervised Classification) gina_prior Uploaded 03-12-2014 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.Bagging_SMO_PolyKernel(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_SMO_PolyKernel(2)_I20
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
0.9302
Per class
Build CPU time
2026.7649
Build memory
194740871.6794
F measure
0.8656
Per class
Kappa
0.7311
KB relative information score
2414.868
Mean absolute error
0.1562
Mean prior absolute error
0.4999
Number of instances
3468
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8657
Per class
Predictive accuracy
0.8656
Prior entropy
0.9998
Recall
0.8656
Per class
Relative absolute error
0.3124
Root mean prior squared error
0.4999
Root mean squared error
0.3187
Root relative squared error
0.6375
SciMark benchmark
901.89