DEVELOPMENT... OpenML
Run
140062

Run 140062

Task 280 (Supervised Classification) heart-h Uploaded 31-12-2014 by Felicia West
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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)_I10
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
0.8818
Per class
Build CPU time
0.117
Build memory
707360568
F measure
0.8131
Per class
Kappa
0.5866
KB relative information score
45.3687
Mean absolute error
0.094
Mean prior absolute error
0.1867
Number of instances
97
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8394
Per class
Predictive accuracy
0.8247
Prior entropy
1.0314
Recall
0.8247
Per class
Relative absolute error
0.5033
Root mean prior squared error
0.3038
Root mean squared error
0.2316
Root relative squared error
0.7626
SciMark benchmark
926.9332