DEVELOPMENT... OpenML
Run
85066

Run 85066

Task 3550 (Supervised Classification) analcatdata_asbestos 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)_I40
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
0.8452
Per class
Build CPU time
0.1601
Build memory
539391509.7831
F measure
0.7475
Per class
Kappa
0.4973
KB relative information score
41.1839
Mean absolute error
0.2479
Mean prior absolute error
0.4943
Number of instances
83
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7587
Per class
Predictive accuracy
0.747
Prior entropy
0.9919
Recall
0.747
Per class
Relative absolute error
0.5015
Root mean prior squared error
0.4971
Root mean squared error
0.4464
Root relative squared error
0.8981
SciMark benchmark
916.7338