DEVELOPMENT... OpenML
Run
125000

Run 125000

Task 3672 (Supervised Classification) kin8nm Uploaded 25-12-2014 by Felicia West
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weka.AdaBoostM1_LWL_DecisionStump(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_LWL_DecisionStump(2)_I10
weka.AdaBoostM1_LWL_DecisionStump(2)_P100
weka.AdaBoostM1_LWL_DecisionStump(2)_S1
weka.AdaBoostM1_LWL_DecisionStump(2)_Wweka.classifiers.lazy.LWL
weka.LWL_DecisionStump(2)_Atrue
weka.LWL_DecisionStump(2)_K-1
weka.LWL_DecisionStump(2)_U0
weka.LWL_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump

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
0.8496
Per class
Build CPU time
4158.2509
Build memory
44810654.9629
F measure
0.7665
Per class
Kappa
0.5332
KB relative information score
3482.1906
Mean absolute error
0.2995
Mean prior absolute error
0.4998
Number of instances
8192
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7671
Per class
Predictive accuracy
0.7665
Prior entropy
0.9998
Recall
0.7665
Per class
Relative absolute error
0.5992
Root mean prior squared error
0.4999
Root mean squared error
0.3997
Root relative squared error
0.7996
SciMark benchmark
937.9119

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