DEVELOPMENT... OpenML
Run
85254

Run 85254

Task 1798 (Supervised Classification) postoperative-patient-data Uploaded 02-12-2014 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
0.3452
Per class
Build CPU time
0.129
Build memory
895578393.6
F measure
0.5566
Per class
Kappa
-0.1202
KB relative information score
-107.3019
Mean absolute error
0.3339
Mean prior absolute error
0.2871
Number of instances
450
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5166
Per class
Predictive accuracy
0.6133
Prior entropy
1.0305
Recall
0.6133
Per class
Relative absolute error
1.1633
Root mean prior squared error
0.3755
Root mean squared error
0.4134
Root relative squared error
1.1009
SciMark benchmark
927.8402