Mercurial > repos > bgruening > sklearn_train_test_eval
diff test-data/pipeline_params18 @ 5:2b8406e74f9e draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
| author | bgruening |
|---|---|
| date | Mon, 16 Dec 2019 05:14:47 -0500 |
| parents | |
| children | ead7adad8d0e |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/pipeline_params18 Mon Dec 16 05:14:47 2019 -0500 @@ -0,0 +1,89 @@ + Parameter Value +* memory memory: None +@ powertransformer powertransformer: PowerTransformer(copy=True, method='yeo-johnson', standardize=True) +* steps "steps: [('powertransformer', PowerTransformer(copy=True, method='yeo-johnson', standardize=True)), ('transformedtargetregressor', TransformedTargetRegressor(check_inverse=True, func=None, inverse_func=None, + regressor=RandomForestRegressor(bootstrap=True, + criterion='mse', + max_depth=None, + max_features='auto', + max_leaf_nodes=None, + min_impurity_decrease=0.0, + min_impurity_split=None, + min_samples_leaf=1, + min_samples_split=2, + min_weight_fraction_leaf=0.0, + n_estimators='warn', + n_jobs=1, + oob_score=False, + random_state=10, + verbose=0, + warm_start=False), + transformer=QuantileTransformer(copy=True, + ignore_implicit_zeros=False, + n_quantiles=1000, + output_distribution='uniform', + random_state=10, + subsample=100000)))]" +@ transformedtargetregressor "transformedtargetregressor: TransformedTargetRegressor(check_inverse=True, func=None, inverse_func=None, + regressor=RandomForestRegressor(bootstrap=True, + criterion='mse', + max_depth=None, + max_features='auto', + max_leaf_nodes=None, + min_impurity_decrease=0.0, + min_impurity_split=None, + min_samples_leaf=1, + min_samples_split=2, + min_weight_fraction_leaf=0.0, + n_estimators='warn', + n_jobs=1, + oob_score=False, + random_state=10, + verbose=0, + warm_start=False), + transformer=QuantileTransformer(copy=True, + ignore_implicit_zeros=False, + n_quantiles=1000, + output_distribution='uniform', + random_state=10, + subsample=100000))" +* verbose verbose: False +@ powertransformer__copy powertransformer__copy: True +@ powertransformer__method powertransformer__method: 'yeo-johnson' +@ powertransformer__standardize powertransformer__standardize: True +@ transformedtargetregressor__check_inverse transformedtargetregressor__check_inverse: True +@ transformedtargetregressor__func transformedtargetregressor__func: None +@ transformedtargetregressor__inverse_func transformedtargetregressor__inverse_func: None +@ transformedtargetregressor__regressor "transformedtargetregressor__regressor: RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None, + max_features='auto', max_leaf_nodes=None, + min_impurity_decrease=0.0, min_impurity_split=None, + min_samples_leaf=1, min_samples_split=2, + min_weight_fraction_leaf=0.0, n_estimators='warn', + n_jobs=1, oob_score=False, random_state=10, verbose=0, + warm_start=False)" +@ transformedtargetregressor__regressor__bootstrap transformedtargetregressor__regressor__bootstrap: True +@ transformedtargetregressor__regressor__criterion transformedtargetregressor__regressor__criterion: 'mse' +@ transformedtargetregressor__regressor__max_depth transformedtargetregressor__regressor__max_depth: None +@ transformedtargetregressor__regressor__max_features transformedtargetregressor__regressor__max_features: 'auto' +@ transformedtargetregressor__regressor__max_leaf_nodes transformedtargetregressor__regressor__max_leaf_nodes: None +@ transformedtargetregressor__regressor__min_impurity_decrease transformedtargetregressor__regressor__min_impurity_decrease: 0.0 +@ transformedtargetregressor__regressor__min_impurity_split transformedtargetregressor__regressor__min_impurity_split: None +@ transformedtargetregressor__regressor__min_samples_leaf transformedtargetregressor__regressor__min_samples_leaf: 1 +@ transformedtargetregressor__regressor__min_samples_split transformedtargetregressor__regressor__min_samples_split: 2 +@ transformedtargetregressor__regressor__min_weight_fraction_leaf transformedtargetregressor__regressor__min_weight_fraction_leaf: 0.0 +@ transformedtargetregressor__regressor__n_estimators transformedtargetregressor__regressor__n_estimators: 'warn' +* transformedtargetregressor__regressor__n_jobs transformedtargetregressor__regressor__n_jobs: 1 +@ transformedtargetregressor__regressor__oob_score transformedtargetregressor__regressor__oob_score: False +@ transformedtargetregressor__regressor__random_state transformedtargetregressor__regressor__random_state: 10 +* transformedtargetregressor__regressor__verbose transformedtargetregressor__regressor__verbose: 0 +@ transformedtargetregressor__regressor__warm_start transformedtargetregressor__regressor__warm_start: False +@ transformedtargetregressor__transformer "transformedtargetregressor__transformer: QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000, + output_distribution='uniform', random_state=10, + subsample=100000)" +@ transformedtargetregressor__transformer__copy transformedtargetregressor__transformer__copy: True +@ transformedtargetregressor__transformer__ignore_implicit_zeros transformedtargetregressor__transformer__ignore_implicit_zeros: False +@ transformedtargetregressor__transformer__n_quantiles transformedtargetregressor__transformer__n_quantiles: 1000 +@ transformedtargetregressor__transformer__output_distribution transformedtargetregressor__transformer__output_distribution: 'uniform' +@ transformedtargetregressor__transformer__random_state transformedtargetregressor__transformer__random_state: 10 +@ transformedtargetregressor__transformer__subsample transformedtargetregressor__transformer__subsample: 100000 + Note: @, params eligible for search in searchcv tool.