Run
437879

Run 437879

Task 7536 (Learning Curve) monks-problems-3 Uploaded 13-05-2015 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)_I10
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.

22 Evaluation measures

Area under ROC curve
0.9814 ± 0.0169
Per class
F measure
0.9639 ± 0.017
Per class
Kappa
0.9278 ± 0.0337
KB relative information score
0.4884 ± 0.0887
Mean absolute error
0.2918 ± 0.0445
Mean prior absolute error
0.4992 ± 0.0003
Number of instances
554
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9646 ± 0.015
Per class
Predictive accuracy
0.9639 ± 0.0169
Prior entropy
0.9989 ± 0.0008
Recall
0.9639 ± 0.0169
Per class
Relative absolute error
0.5845 ± 0.0891
Root mean prior squared error
0.4996 ± 0.0003
Root mean squared error
0.3097 ± 0.0384
Root relative squared error
0.62 ± 0.0769
SciMark benchmark
913.9348
UserCPU time millis
10
UserCPU time millis training
10