Run
437877

Run 437877

Task 7532 (Learning Curve) monks-problems-1 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
1
Per class
F measure
0.8982 ± 0.141
Per class
Kappa
0.7986 ± 0.2636
KB relative information score
0.2752 ± 0.0189
Mean absolute error
0.3897 ± 0.0063
Mean prior absolute error
0.5
Number of instances
556
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9162 ± 0.0871
Per class
Predictive accuracy
0.8993 ± 0.1317
Prior entropy
1
Recall
0.8993 ± 0.1317
Per class
Relative absolute error
0.7794 ± 0.0125
Root mean prior squared error
0.5
Root mean squared error
0.3984 ± 0.009
Root relative squared error
0.7968 ± 0.018
SciMark benchmark
913.9348
UserCPU time millis
10
UserCPU time millis training
10