Run
10229156

Run 10229156

Task 32 (Supervised Classification) pendigits Uploaded 11-07-2019 by Prabhant Singh
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sk learn.tree.tree.DecisionTreeClassifier)(5)Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(44)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(44)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(44)_max_depthnull
sklearn.tree.tree.DecisionTreeClassifier(44)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(44)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(44)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(44)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(44)_min_samples_leaf1
sklearn.tree.tree.DecisionTreeClassifier(44)_min_samples_split2
sklearn.tree.tree.DecisionTreeClassifier(44)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(44)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(44)_random_state42090
sklearn.tree.tree.DecisionTreeClassifier(44)_splitter"best"
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(5)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(5)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.impute.SimpleImputer(13)_copytrue
sklearn.impute.SimpleImputer(13)_fill_valuenull
sklearn.impute.SimpleImputer(13)_missing_valuesNaN
sklearn.impute.SimpleImputer(13)_strategy"mean"
sklearn.impute.SimpleImputer(13)_verbose0

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
0.9796 ± 0.004
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9633 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9593 ± 0.0081
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9616 ± 0.0077
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0073 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
10992
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9633 ± 0.0071
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9633 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3208 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Recall
0.9633 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0407 ± 0.0081
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0856 ± 0.0082
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2855 ± 0.0274
Cross-validation details (10-fold Crossvalidation)