DEVELOPMENT... OpenML
Run
148494

Run 148494

Task 3947 (Supervised Classification) KDDCup99 Uploaded 03-02-2015 by Felicia West
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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.

22 Evaluation measures

Area under ROC curve
1
Per class
F measure
0.9993
Per class
Kappa
0.9988
KB relative information score
492767.9979
Mean absolute error
0.0001
Mean prior absolute error
0.0514
Number of instances
494020
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9993
Per class
Predictive accuracy
0.9993
Prior entropy
1.5581
Recall
0.9993
Per class
Relative absolute error
0.0016
Root mean prior squared error
0.1603
Root mean squared error
0.0072
Root relative squared error
0.0447
SciMark benchmark
934.5243
UserCPU time millis
14232650
UserCPU time millis testing
1974990
UserCPU time millis training
12257660