Run
8917000

Run 8917000

Task 14 (Supervised Classification) mfeat-fourier 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[]
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_features0.05447849460498477
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_leaf15
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split17
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[]
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.

17 Evaluation measures

Area under ROC curve
0.9779 ± 0.0027
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8077 ± 0.0277
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7906 ± 0.0301
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1230.2239 ± 2.2531
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1075 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8076 ± 0.027
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8115 ± 0.0271
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.8115 ± 0.0271
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5971 ± 0.0104
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2011 ± 0.003
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6703 ± 0.0101
Cross-validation details (10-fold Crossvalidation)