Repository revision
15:b94babda32e4

Repository 'sklearn_stacking_ensemble_models'
hg clone https://toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models

Stacking Ensembles tool metadata
Miscellaneous
builds stacking, voting ensemble models with numerous base options
sklearn_stacking_ensemble_models
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/1.0.8.4
1.0.8.4
echo "$ENSEMBLE_VERSION"
True
Version lineage of this tool (guids ordered most recent to oldest)
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/1.0.8.4 (this tool)
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/1.0.8.3
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/1.0.8.2
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/1.0.8.1
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/0.2.0.1
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/0.2.0
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_stacking_ensemble_models/sklearn_stacking_ensemble_models/0.1.0
sklearn_stacking_ensemble_models
Requirements (dependencies defined in the <requirements> tag set)
name version type
Galaxy-ML 0.8.3 package
Additional information about this tool
#for $i, $base in enumerate($base_est_builder)
        #if $i == 0
            #if $base.estimator_selector.selected_module == 'custom_estimator'
            bases='${base.estimator_selector.c_estimator}';
            #else
            bases='None';
            #end if
        #elif $base.estimator_selector.selected_module == 'custom_estimator'
        bases="\$bases,${base.estimator_selector.c_estimator}";
        #else
        bases="\$bases,None";
        #end if
        #end for
        python '$__tool_directory__/stacking_ensembles.py'
            --inputs '$inputs'
            --outfile '$outfile'
            --bases "\$bases"
            #if $algo_selection.estimator_type not in ('sklearn.ensemble_VotingClassifier', 'sklearn.ensemble_VotingRegressor')
            #if $algo_selection.meta_estimator.estimator_selector.selected_module == 'custom_estimator'
            --meta '${algo_selection.meta_estimator.estimator_selector.c_estimator}'
            #end if
            #end if
            #if $get_params
            --outfile_params '$outfile_params'
            #end if
        
    
None
False
Functional tests
name inputs outputs required files
Test-1 algo_selection|options|weights: [1, 2]
algo_selection|estimator_type: sklearn.ensemble_VotingClassifier
base_est_builder_0|estimator_selector|selected_estimator: SVC
base_est_builder_0|estimator_selector|selected_module: svm
base_est_builder_1|estimator_selector|selected_estimator: XGBClassifier
base_est_builder_1|estimator_selector|selected_module: xgboost
get_params: False
name: value
value
Test-2 algo_selection|meta_estimator|estimator_selector|c_estimator: LinearRegression01.zip
algo_selection|meta_estimator|estimator_selector|selected_module: custom_estimator
algo_selection|estimator_type: mlxtend.regressor_StackingCVRegressor
base_est_builder_0|estimator_selector|c_estimator: RandomForestRegressor01.zip
base_est_builder_0|estimator_selector|selected_module: custom_estimator
base_est_builder_1|estimator_selector|c_estimator: XGBRegressor01.zip
base_est_builder_1|estimator_selector|selected_module: custom_estimator
get_params: False
name: value
LinearRegression01.zip
RandomForestRegressor01.zip
XGBRegressor01.zip
value
Test-3 algo_selection|meta_estimator|estimator_selector|selected_estimator: SVR
algo_selection|meta_estimator|estimator_selector|selected_module: svm
algo_selection|estimator_type: mlxtend.regressor_StackingRegressor
base_est_builder_0|estimator_selector|c_estimator: RandomForestRegressor01.zip
base_est_builder_0|estimator_selector|selected_module: custom_estimator
base_est_builder_1|estimator_selector|selected_estimator: XGBRegressor
base_est_builder_1|estimator_selector|selected_module: xgboost
get_params: False
name: value
RandomForestRegressor01.zip
value