OpenML
311300

Run 311300

Task 70 (Learning Curve) balance-scale Uploaded 20-03-2015 by Joaquin Vanschoren
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Flow

weka.RandomSubSpace_REPTree(4)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(9)_M2
weka.REPTree(9)_V0.001
weka.REPTree(9)_N3
weka.REPTree(9)_S1
weka.REPTree(9)_L-1
weka.REPTree(9)_I0.0
weka.RandomSubSpace_REPTree(4)_P0.5
weka.RandomSubSpace_REPTree(4)_S1
weka.RandomSubSpace_REPTree(4)_num-slots1
weka.RandomSubSpace_REPTree(4)_I40
weka.RandomSubSpace_REPTree(4)_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.

20 Evaluation measures

Area under ROC curve
0.9235 ± 0.0225
Per class
Kappa
0.7083 ± 0.0739
KB relative information score
0.252 ± 0.0223
Mean absolute error
0.2953 ± 0.008
Mean prior absolute error
0.3798 ± 0.0012
Number of instances
6250
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Predictive accuracy
0.8427 ± 0.04
Prior entropy
1.3181 ± 0.0119
Recall
0.8427 ± 0.04
Per class
Relative absolute error
0.7775 ± 0.0206
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.3522 ± 0.0087
Root relative squared error
0.8085 ± 0.0193
SciMark benchmark
1331.3129
UserCPU time millis
50
UserCPU time millis testing
10
UserCPU time millis training
40