DEVELOPMENT... OpenML
Run
20761

Run 20761

Task 49 (Supervised Classification) tic-tac-toe Uploaded 18-06-2014 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)_I10
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
0.9973
Per class
F measure
0.9832
Per class
Kappa
0.9627
KB relative information score
920.8773
Mean absolute error
0.0167
Mean prior absolute error
0.453
Number of instances
958
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9837
Per class
Predictive accuracy
0.9833
Prior entropy
0.9312
Recall
0.9833
Per class
Relative absolute error
0.0369
Root mean prior squared error
0.4759
Root mean squared error
0.1292
Root relative squared error
0.2715
SciMark benchmark
944.3165[556.02186590270571013.1203667026068482.5806157404377909.2750179897271760.5845701777503]