DEVELOPMENT... OpenML
Run
122611

Run 122611

Task 3705 (Supervised Classification) autoHorse Uploaded 14-12-2014 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)_I160
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
0.9838
Per class
Build CPU time
49.8989
Build memory
94905488.1561
F measure
0.9854
Per class
Kappa
0.9696
KB relative information score
198.5742
Mean absolute error
0.0146
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
0.9854
Per class
Predictive accuracy
0.9854
Prior entropy
0.9742
Recall
0.9854
Per class
Relative absolute error
0.0304
Root mean prior squared error
0.4909
Root mean squared error
0.121
Root relative squared error
0.2464
SciMark benchmark
923.9118