Run
8661895

Run 8661895

Task 3567 (Supervised Classification) collins Uploaded 21-12-2017 by Vishal Chouskey
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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.ensemble.forest.RandomForestClassifier)(4)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(14)_categorical_features[19, 20]
sklearn.preprocessing.data.OneHotEncoder(14)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(14)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(14)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(14)_sparsetrue
sklearn.ensemble.forest.RandomForestClassifier(29)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(29)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(29)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(29)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(29)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(29)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(29)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(29)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(29)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(29)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(29)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(29)_random_state1
sklearn.ensemble.forest.RandomForestClassifier(29)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(29)_warm_startfalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(9)_threshold0.0
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[19, 20]
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

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
0.9996 ± 0.0008
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9782
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9802 ± 0.0193
Cross-validation details (10-fold Crossvalidation)
KB relative information score
452.4029 ± 0.6262
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0237 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1212 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Number of instances
500
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9792
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.982 ± 0.0175
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.6642
Cross-validation details (10-fold Crossvalidation)
Recall
0.982 ± 0.0175
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1959 ± 0.0256
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.246 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.075 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3047 ± 0.0339
Cross-validation details (10-fold Crossvalidation)