Run
503671

Run 503671

Task 10059 (Learning Curve) ipums_la_99-small Uploaded 29-12-2015 by Joaquin Vanschoren
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Flow

weka.FURIA(2)Jens Christian Huehn, Eyke Huellermeier (2009). FURIA: An Algorithm for Unordered Fuzzy Rule Induction. Data Mining and Knowledge Discovery..
weka.FURIA(2)_F3
weka.FURIA(2)_N2.0
weka.FURIA(2)_O2
weka.FURIA(2)_S1
weka.FURIA(2)_s0
weka.FURIA(2)_p0

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
0.633 ± 0.0382
Per class
F measure
0.92 ± 0.0058
Per class
Kappa
0.2173 ± 0.0602
KB relative information score
1682.4619 ± 64.232
Mean absolute error
0.0668 ± 0.0047
Mean prior absolute error
0.1203 ± 0.0004
Number of instances
8844
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9166 ± 0.0082
Per class
Predictive accuracy
0.936 ± 0.0044
Prior entropy
0.3444
Recall
0.936 ± 0.0044
Per class
Relative absolute error
0.5555 ± 0.0378
Root mean prior squared error
0.2452 ± 0.0008
Root mean squared error
0.2463 ± 0.0092
Root relative squared error
1.0048 ± 0.037
SciMark benchmark
943.5627
UserCPU time millis
7050
UserCPU time millis testing
10
UserCPU time millis training
7040