DEVELOPMENT... OpenML
Run
86393

Run 86393

Task 2355 (Supervised Classification) meta_instanceincremental.arff 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)_I10
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
0.9126
Per class
Build CPU time
0.198
Build memory
1235659736
F measure
0.9148
Per class
Kappa
0.8161
KB relative information score
-1.0344
Mean absolute error
0.2681
Mean prior absolute error
0.2324
Number of instances
24
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.925
Per class
Predictive accuracy
0.9167
Prior entropy
1.3146
Recall
0.9167
Per class
Relative absolute error
1.1536
Root mean prior squared error
0.3388
Root mean squared error
0.324
Root relative squared error
0.9565
SciMark benchmark
938.2568