Run
504033

Run 504033

Task 10057 (Learning Curve) kdd_ipums_la_97-small Uploaded 30-12-2015 by Joaquin Vanschoren
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Flow

weka.VotedPerceptron(5)Y. Freund, R. E. Schapire: Large margin classification using the perceptron algorithm. In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998.
weka.VotedPerceptron(5)_I1
weka.VotedPerceptron(5)_E1.0
weka.VotedPerceptron(5)_S1
weka.VotedPerceptron(5)_M10000

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
0.6769 ± 0.0113
Per class
F measure
0.7205 ± 0.0116
Per class
Kappa
0.3935 ± 0.0231
KB relative information score
3089.8417 ± 13.1537
Mean absolute error
0.2531 ± 0.0085
Mean prior absolute error
0.466 ± 0.0002
Number of instances
7019
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7629 ± 0.0148
Per class
Predictive accuracy
0.7468 ± 0.0085
Prior entropy
0.9504
Recall
0.7468 ± 0.0085
Per class
Relative absolute error
0.5432 ± 0.0182
Root mean prior squared error
0.4827 ± 0.0002
Root mean squared error
0.503 ± 0.0084
Root relative squared error
1.042 ± 0.0174
SciMark benchmark
929.0201
UserCPU time millis
61680
UserCPU time millis testing
42190
UserCPU time millis training
19490