Run
8777908

Run 8777908

Task 31 (Supervised Classification) credit-g 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, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
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, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"median"
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_depth1.7356628514287638
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_leaf13
sklearn.tree.tree.DecisionTreeClassifier(20)_min_samples_split6
sklearn.tree.tree.DecisionTreeClassifier(20)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(20)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(20)_random_state8075
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.

15 Evaluation measures

Area under ROC curve
0.6506 ± 0.0396
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
60.9412 ± 4.3775
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3766 ± 0.0139
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.7
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8963 ± 0.0332
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4341 ± 0.0109
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9472 ± 0.0238
Cross-validation details (10-fold Crossvalidation)