DEVELOPMENT... OpenML
Run
140178

Run 140178

Task 3055 (Supervised Classification) monks-problems-3 Uploaded 31-12-2014 by Jason
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.9922
Per class
Build CPU time
0.21
Build memory
567321304
F measure
0.9781
Per class
Kappa
0.9552
KB relative information score
168.8145
Mean absolute error
0.0361
Mean prior absolute error
0.4967
Number of instances
182
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9791
Per class
Predictive accuracy
0.978
Prior entropy
0.9989
Recall
0.978
Per class
Relative absolute error
0.0727
Root mean prior squared error
0.4971
Root mean squared error
0.1306
Root relative squared error
0.2627
SciMark benchmark
945.1987