DEVELOPMENT... OpenML
Run
19723

Run 19723

Task 29 (Supervised Classification) credit-approval Uploaded 16-06-2014 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)_I20
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
0.9112
Per class
F measure
0.8495
Per class
Kappa
0.696
KB relative information score
472.6051
Mean absolute error
0.1555
Mean prior absolute error
0.494
Number of instances
690
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8503
Per class
Predictive accuracy
0.8493
Prior entropy
0.9913
Recall
0.8493
Per class
Relative absolute error
0.3149
Root mean prior squared error
0.497
Root mean squared error
0.3644
Root relative squared error
0.7332
SciMark benchmark
925.1212[556.9095328849074989.704664392416471.76705325224475887.12008669237921720.1048835431066]