Run
8777839

Run 8777839

Task 34537 (Supervised Classification) PhishingWebsites Uploaded 05-01-2018 by Vishal Chouskey
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  • openml-pimp openml-python Sklearn_0.18.2.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.tree.tree.DecisionTreeClassifier)(3)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(14)_categorical_features[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
sklearn.preprocessing.data.OneHotEncoder(14)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(14)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(14)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(14)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(9)_threshold0.0
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"mean"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.tree.tree.DecisionTreeClassifier(20)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(20)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(20)_max_depth1.7754792493660159
sklearn.tree.tree.DecisionTreeClassifier(20)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(20)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(20)_min_impurity_split1e-07
sklearn.tree.tree.DecisionTreeClassifier(20)_min_samples_leaf2
sklearn.tree.tree.DecisionTreeClassifier(20)_min_samples_split8
sklearn.tree.tree.DecisionTreeClassifier(20)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(20)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(20)_random_state62093
sklearn.tree.tree.DecisionTreeClassifier(20)_splitter"best"

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.

17 Evaluation measures

Area under ROC curve
0.88 ± 0.0067
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8887 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7741 ± 0.0123
Cross-validation details (10-fold Crossvalidation)
KB relative information score
7077.7189 ± 10.0536
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1975 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4935 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
11055
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8889 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8889 ± 0.0059
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9906
Cross-validation details (10-fold Crossvalidation)
Recall
0.8889 ± 0.0059
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4002 ± 0.0083
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4967 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3143 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6326 ± 0.0147
Cross-validation details (10-fold Crossvalidation)