DEVELOPMENT... OpenML
Run
50846

Run 50846

Task 2098 (Learning Curve) abalone Uploaded 06-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.RandomSubSpace_REPTree(2)Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html.
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.RandomSubSpace_REPTree(2)_P0.5
weka.RandomSubSpace_REPTree(2)_S1
weka.RandomSubSpace_REPTree(2)_num-slots1
weka.RandomSubSpace_REPTree(2)_I10
weka.RandomSubSpace_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.

19 Evaluation measures

Area under ROC curve
0.7591 ± 0.0078
Per class
Build CPU time
0.0525
Build memory
495198827.4462
Kappa
0.1605 ± 0.0243
KB relative information score
0.2395 ± 0.0102
Mean absolute error
0.0564 ± 0.0002
Mean prior absolute error
0.0618 ± 0
Number of instances
4177
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Predictive accuracy
0.2662 ± 0.0208
Prior entropy
3.6031 ± 0.0188
Recall
0.2662 ± 0.0208
Per class
Relative absolute error
0.9126 ± 0.0038
Root mean prior squared error
0.1757 ± 0
Root mean squared error
0.1681 ± 0.0007
Root relative squared error
0.9564 ± 0.004
SciMark benchmark
1955.1311