Run
435409

Run 435409

Task 89 (Learning Curve) page-blocks Uploaded 12-05-2015 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)_I160
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
0.9917 ± 0.0048
Per class
F measure
0.9687 ± 0.0064
Per class
Kappa
0.8373 ± 0.0333
KB relative information score
0.7379 ± 0.0301
Mean absolute error
0.0234 ± 0.0018
Mean prior absolute error
0.0762 ± 0.0003
Number of instances
54730
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9697 ± 0.0063
Per class
Predictive accuracy
0.971 ± 0.0058
Prior entropy
0.6355 ± 0.0053
Recall
0.971 ± 0.0058
Per class
Relative absolute error
0.3071 ± 0.0241
Root mean prior squared error
0.1948 ± 0.0007
Root mean squared error
0.0941 ± 0.0071
Root relative squared error
0.4827 ± 0.0367
SciMark benchmark
934.8058
UserCPU time millis
5350
UserCPU time millis testing
510
UserCPU time millis training
4840