DEVELOPMENT... OpenML
Run
61604

Run 61604

Task 1702 (Learning Curve) kr-vs-kp Uploaded 16-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_RandomForest(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1
weka.MultiBoostAB_RandomForest(2)_C3
weka.MultiBoostAB_RandomForest(2)_P100
weka.MultiBoostAB_RandomForest(2)_S1
weka.MultiBoostAB_RandomForest(2)_I10
weka.MultiBoostAB_RandomForest(2)_Wweka.classifiers.trees.RandomForest

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
0.9993 ± 0.0008
Per class
Build CPU time
0.1022
Build memory
1550572237.6667
F measure
0.9922 ± 0.0045
Per class
Kappa
0.9843 ± 0.009
KB relative information score
0.9112 ± 0.0056
Mean absolute error
0.0544 ± 0.0029
Mean prior absolute error
0.499 ± 0.0001
Number of instances
3196
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9922 ± 0.0044
Per class
Predictive accuracy
0.9922 ± 0.0045
Prior entropy
0.9986 ± 0.0002
Recall
0.9922 ± 0.0045
Per class
Relative absolute error
0.109 ± 0.0058
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.106 ± 0.0077
Root relative squared error
0.2122 ± 0.0155
SciMark benchmark
1707.2836