Run
8858278

Run 8858278

Task 146800 (Supervised Classification) MiceProtein Uploaded 21-02-2018 by Jan van Rijn
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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.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[]
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.preprocessing.data.OneHotEncoder(18)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.linear_model.logistic.LogisticRegression(12)_C1.0
sklearn.linear_model.logistic.LogisticRegression(12)_class_weightnull
sklearn.linear_model.logistic.LogisticRegression(12)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(12)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(12)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(12)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(12)_multi_class"ovr"
sklearn.linear_model.logistic.LogisticRegression(12)_n_jobs1
sklearn.linear_model.logistic.LogisticRegression(12)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(12)_random_state1
sklearn.linear_model.logistic.LogisticRegression(12)_solver"liblinear"
sklearn.linear_model.logistic.LogisticRegression(12)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(12)_verbose0
sklearn.linear_model.logistic.LogisticRegression(12)_warm_startfalse

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
0.9875 ± 0.005
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.869 ± 0.0302
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8517 ± 0.0353
Cross-validation details (10-fold Crossvalidation)
KB relative information score
784.892 ± 1.0624
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0998 ± 0.0021
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2185 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
1080
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8731 ± 0.0279
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8704 ± 0.0309
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.9931
Cross-validation details (10-fold Crossvalidation)
Recall
0.8704 ± 0.0309
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4569 ± 0.0094
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3305 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1853 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.5607 ± 0.0127
Cross-validation details (10-fold Crossvalidation)