DEVELOPMENT... OpenML
Run
47810

Run 47810

Task 91 (Learning Curve) pendigits Uploaded 05-11-2014 by Jason
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  • curves weka weka_3.7.12-SNAPSHOT
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Flow

weka.Bagging_REPTree(3)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_REPTree(3)_I10
weka.Bagging_REPTree(3)_P100
weka.Bagging_REPTree(3)_S1
weka.Bagging_REPTree(3)_Wweka.classifiers.trees.REPTree
weka.Bagging_REPTree(3)_num-slots1
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

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
0.9991 ± 0.0005
Per class
Build CPU time
0.1523
Build memory
2605588862.26
F measure
0.9777 ± 0.0046
Per class
Kappa
0.9752 ± 0.0051
KB relative information score
0.9598 ± 0.0032
Mean absolute error
0.0135 ± 0.0008
Mean prior absolute error
0.18 ± 0
Number of instances
109920
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9778 ± 0.0045
Per class
Predictive accuracy
0.9777 ± 0.0046
Prior entropy
3.3208 ± 0.0002
Recall
0.9777 ± 0.0046
Per class
Relative absolute error
0.0752 ± 0.0047
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.0649 ± 0.0037
Root relative squared error
0.2164 ± 0.0124
SciMark benchmark
1631.9056