DEVELOPMENT... OpenML
Run
16575

Run 16575

Task 50 (Supervised Classification) heart-h Uploaded 04-06-2014 by Felicia West
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Flow

weka.MultiBoostAB_SMO_PolyKernel(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_SMO_PolyKernel(1)_C3
weka.MultiBoostAB_SMO_PolyKernel(1)_I160
weka.MultiBoostAB_SMO_PolyKernel(1)_P100
weka.MultiBoostAB_SMO_PolyKernel(1)_S1
weka.MultiBoostAB_SMO_PolyKernel(1)_Wweka.classifiers.functions.SMO
weka.SMO_PolyKernel(5)_C1.0
weka.SMO_PolyKernel(5)_L0.001
weka.SMO_PolyKernel(5)_N0
weka.SMO_PolyKernel(5)_P1.0E-12
weka.SMO_PolyKernel(5)_V-1
weka.SMO_PolyKernel(5)_W1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.894
Per class
F measure
0.8425
Per class
Kappa
0.6564
KB relative information score
143.2563
Mean absolute error
0.0927
Mean prior absolute error
0.1867
Number of instances
294
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8422
Per class
Predictive accuracy
0.8435
Prior entropy
1.0314
Recall
0.8435
Per class
Relative absolute error
0.4967
Root mean prior squared error
0.3037
Root mean squared error
0.2203
Root relative squared error
0.7253
SciMark benchmark
943.6497[559.23073532101811014.4538012229739478.92144908848445906.7589715622941758.8835103978397]