DEVELOPMENT... OpenML
Run
124826

Run 124826

Task 3705 (Supervised Classification) autoHorse 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)_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
0.9961
Per class
Build CPU time
2.9032
Build memory
719590399.3756
F measure
0.9609
Per class
Kappa
0.9187
KB relative information score
189.6166
Mean absolute error
0.0351
Mean prior absolute error
0.4821
Number of instances
205
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.961
Per class
Predictive accuracy
0.961
Prior entropy
0.9742
Recall
0.961
Per class
Relative absolute error
0.0729
Root mean prior squared error
0.4909
Root mean squared error
0.1773
Root relative squared error
0.3612
SciMark benchmark
890.3066