Run
1665117

Run 1665117

Task 34537 (Supervised Classification) PhishingWebsites Uploaded 19-07-2016 by Jan van Rijn
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Flow

weka.Winnow(4)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(4)_I1
weka.Winnow(4)_A2.0
weka.Winnow(4)_B0.5
weka.Winnow(4)_H-1.0
weka.Winnow(4)_W2.0
weka.Winnow(4)_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.

17 Evaluation measures

Area under ROC curve
0.83
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8231
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6474
Cross-validation details (10-fold Crossvalidation)
KB relative information score
7058.5855
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1774
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4935
Cross-validation details (10-fold Crossvalidation)
Number of instances
11055
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8351
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8226
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9906
Cross-validation details (10-fold Crossvalidation)
Recall
0.8226
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3594
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4967
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4212
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8479
Cross-validation details (10-fold Crossvalidation)