Run
10452016

Run 10452016

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 13-04-2020 by Heinrich Peters
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, standardscaler=sklearn.preprocessing.data.StandardScaler,randomforestclassi fier=sklearn.ensemble.forest.RandomForestClassifier)(2)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"median"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.preprocessing.data.StandardScaler(29)_copytrue
sklearn.preprocessing.data.StandardScaler(29)_with_meantrue
sklearn.preprocessing.data.StandardScaler(29)_with_stdtrue
sklearn.ensemble.forest.RandomForestClassifier(63)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(63)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(63)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(63)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(63)_max_features0.4197778768858397
sklearn.ensemble.forest.RandomForestClassifier(63)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(63)_min_impurity_decrease0
sklearn.ensemble.forest.RandomForestClassifier(63)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(63)_min_samples_leaf12
sklearn.ensemble.forest.RandomForestClassifier(63)_min_samples_split5
sklearn.ensemble.forest.RandomForestClassifier(63)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(63)_n_estimators300
sklearn.ensemble.forest.RandomForestClassifier(63)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(63)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(63)_random_state1
sklearn.ensemble.forest.RandomForestClassifier(63)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(63)_warm_startfalse
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(2)_verbosefalse

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.

18 Evaluation measures

Area under ROC curve
0.7312 ± 0.0591
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7457 ± 0.0392
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.248 ± 0.1162
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.1051 ± 0.047
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3124 ± 0.0118
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.7794 ± 0.0249
Cross-validation details (10-fold Crossvalidation)
Number of instances
748
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7502 ± 0.0492
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7794 ± 0.0249
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8605 ± 0.0315
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3948 ± 0.0146
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.927 ± 0.0333
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.6003 ± 0.0497
Cross-validation details (10-fold Crossvalidation)