Run
142449

Run 142449

Task 285 (Supervised Classification) vote Uploaded 04-01-2015 by Joaquin Vanschoren
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)_I160
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
0.979
Per class
Cross-validation details (33% Holdout set)
Build CPU time
0.7
Cross-validation details (33% Holdout set)
Build memory
432764896
Cross-validation details (33% Holdout set)
F measure
0.972
Per class
Cross-validation details (33% Holdout set)
Kappa
0.9409
Cross-validation details (33% Holdout set)
KB relative information score
134.1634
Cross-validation details (33% Holdout set)
Mean absolute error
0.028
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.4739
Cross-validation details (33% Holdout set)
Number of instances
143
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.972
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.972
Cross-validation details (33% Holdout set)
Prior entropy
0.9627
Cross-validation details (33% Holdout set)
Recall
0.972
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.059
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4865
Cross-validation details (33% Holdout set)
Root mean squared error
0.1667
Cross-validation details (33% Holdout set)
Root relative squared error
0.3427
Cross-validation details (33% Holdout set)
SciMark benchmark
941.9296