Run
200740

Run 200740

Task 4590 (Supervised Classification) mfeat-pixel Uploaded 27-02-2015 by Joaquin Vanschoren
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Flow

weka.Winnow(3)N. Littlestone (1988). Learning quickly when irrelevant attributes are abound: A new linear threshold algorithm. Machine Learning. 2:285-318. N. Littlestone (1989). Mistake bounds and logarithmic linear-threshold learning algorithms. University of California, Santa Cruz.
weka.Winnow(3)_I1
weka.Winnow(3)_A2.0
weka.Winnow(3)_B0.5
weka.Winnow(3)_H-1.0
weka.Winnow(3)_W2.0
weka.Winnow(3)_S1

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
0.9529
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.9829
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.9051
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
17423.5184
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.0171
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.1803
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
20000
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.9829
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.9829
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
0.4703
Cross-validation details (10 times 10-fold Crossvalidation)
Recall
0.9829
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.0948
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.1308
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
0.4359
Cross-validation details (10 times 10-fold Crossvalidation)
SciMark benchmark
1404.1865
UserCPU time millis
70
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis testing
30
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis training
40
Cross-validation details (10 times 10-fold Crossvalidation)