DEVELOPMENT... OpenML
Run
55405

Run 55405

Task 1764 (Learning Curve) electricity Uploaded 11-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I10
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

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
0.9672 ± 0.0026
Per class
Build CPU time
0.764
Build memory
2344448581.48
F measure
0.9062 ± 0.0057
Per class
Kappa
0.8078 ± 0.0115
KB relative information score
0.8053 ± 0.0115
Mean absolute error
0.0944 ± 0.0055
Mean prior absolute error
0.4886 ± 0
Number of instances
45312
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9062 ± 0.0056
Per class
Predictive accuracy
0.9063 ± 0.0057
Prior entropy
0.9835 ± 0
Recall
0.9063 ± 0.0057
Per class
Relative absolute error
0.1931 ± 0.0113
Root mean prior squared error
0.4943 ± 0
Root mean squared error
0.2902 ± 0.0083
Root relative squared error
0.587 ± 0.0168
SciMark benchmark
1525.9265