Run
8916936

Run 8916936

Task 10 (Supervised Classification) lymph Uploaded 30-03-2018 by Hilde Weerts
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  • openml-python Sklearn_0.19.1. study_98
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Flow

sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.Condition alImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethre shold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sk learn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features[0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 16]
sklearn.preprocessing.data.OneHotEncoder(17)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(32)_criterion"entropy"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(32)_max_features0.4985070123025904
sklearn.ensemble.forest.RandomForestClassifier(32)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_leaf18
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split19
sklearn.ensemble.forest.RandomForestClassifier(32)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_n_estimators500
sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(32)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state1
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_warm_startfalse
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull
hyperimp.utils.preprocessing.ConditionalImputer(1)_axis0
hyperimp.utils.preprocessing.ConditionalImputer(1)_categorical_features[0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 16]
hyperimp.utils.preprocessing.ConditionalImputer(1)_copytrue
hyperimp.utils.preprocessing.ConditionalImputer(1)_fill_empty0
hyperimp.utils.preprocessing.ConditionalImputer(1)_missing_values"NaN"
hyperimp.utils.preprocessing.ConditionalImputer(1)_strategy"mean"
hyperimp.utils.preprocessing.ConditionalImputer(1)_strategy_nominal"most_frequent"
hyperimp.utils.preprocessing.ConditionalImputer(1)_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.

15 Evaluation measures

Area under ROC curve
0.9045 ± 0.0405
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5481 ± 0.1641
Cross-validation details (10-fold Crossvalidation)
KB relative information score
47.3505 ± 0.801
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1862 ± 0.0148
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2677 ± 0.0078
Cross-validation details (10-fold Crossvalidation)
Number of instances
148
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7703 ± 0.0772
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.2818
Cross-validation details (10-fold Crossvalidation)
Recall
0.7703 ± 0.0772
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6956 ± 0.0481
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3639 ± 0.0108
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2825 ± 0.0225
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7762 ± 0.057
Cross-validation details (10-fold Crossvalidation)