Run
10560435

Run 10560435

Task 14952 (Supervised Classification) PhishingWebsites Uploaded 14-08-2021 by Sergey Redyuk
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Flow

sklearn.tree.tree.ExtraTreeClassifier(28)An extremely randomized tree classifier. Extra-trees differ from classic decision trees in the way they are built. When looking for the best split to separate the samples of a node into two groups, random splits are drawn for each of the `max_features` randomly selected features and the best split among those is chosen. When `max_features` is set 1, this amounts to building a totally random decision tree. Warning: Extra-trees should only be used within ensemble methods.
sklearn.tree.tree.ExtraTreeClassifier(28)_class_weightnull
sklearn.tree.tree.ExtraTreeClassifier(28)_criterion"gini"
sklearn.tree.tree.ExtraTreeClassifier(28)_max_depth1000
sklearn.tree.tree.ExtraTreeClassifier(28)_max_features"auto"
sklearn.tree.tree.ExtraTreeClassifier(28)_max_leaf_nodesnull
sklearn.tree.tree.ExtraTreeClassifier(28)_min_impurity_split1e-07
sklearn.tree.tree.ExtraTreeClassifier(28)_min_samples_leaf1
sklearn.tree.tree.ExtraTreeClassifier(28)_min_samples_split2
sklearn.tree.tree.ExtraTreeClassifier(28)_min_weight_fraction_leaf0.0
sklearn.tree.tree.ExtraTreeClassifier(28)_random_state16971
sklearn.tree.tree.ExtraTreeClassifier(28)_splitter"random"

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

18 Evaluation measures

Area under ROC curve
0.9744 ± 0.0046
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9633 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9255 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9246 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0372 ± 0.0049
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4935 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9633 ± 0.0061
Cross-validation details (10-fold Crossvalidation)
Number of instances
11055
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9633 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9633 ± 0.0061
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9906 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0754 ± 0.0099
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4967 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1757 ± 0.0136
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3538 ± 0.0274
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9622 ± 0.0064
Cross-validation details (10-fold Crossvalidation)