Run
8916645

Run 8916645

Task 14 (Supervised Classification) mfeat-fourier Uploaded 30-03-2018 by Hilde Weerts
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • openml-python Sklearn_0.19.1. study_98
Issue #Downvotes for this reason By


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)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(32)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(32)_max_features0.2732507074025541
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_leaf14
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split12
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
0.9821 ± 0.0027
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8208 ± 0.0219
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8017 ± 0.0244
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1521.294 ± 1.9816
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.07 ± 0.0016
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
0.8211 ± 0.0216
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8215 ± 0.022
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.8215 ± 0.022
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.389 ± 0.009
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1649 ± 0.0047
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5496 ± 0.0155
Cross-validation details (10-fold Crossvalidation)