DEVELOPMENT... OpenML
Run
124649

Run 124649

Task 3896 (Supervised Classification) ada_agnostic Uploaded 24-12-2014 by Felicia West
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Flow

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)_I20
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
0.8866
Per class
Build CPU time
5046.1947
Build memory
71416403.6984
F measure
0.8368
Per class
Kappa
0.5471
KB relative information score
1897.445
Mean absolute error
0.2064
Mean prior absolute error
0.3732
Number of instances
4562
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8369
Per class
Predictive accuracy
0.8441
Prior entropy
0.8085
Recall
0.8441
Per class
Relative absolute error
0.5531
Root mean prior squared error
0.4319
Root mean squared error
0.3336
Root relative squared error
0.7724
SciMark benchmark
908.8705