view test-data/get_params09.tabular @ 14:f73a2b68a37b draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author bgruening
date Wed, 09 Aug 2023 14:37:52 +0000
parents eaddff553324
children
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	Parameter	Value
*	memory	memory: None
*	steps	"steps: [('relieff', ReliefF(discrete_threshold=10, n_features_to_select=3, n_jobs=1,
    n_neighbors=100, verbose=False)), ('randomforestregressor', 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=None, verbose=0, warm_start=False))]"
@	relieff	"relieff: ReliefF(discrete_threshold=10, n_features_to_select=3, n_jobs=1,
    n_neighbors=100, verbose=False)"
@	randomforestregressor	"randomforestregressor: 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=None, verbose=0, warm_start=False)"
@	relieff__discrete_threshold	relieff__discrete_threshold: 10
@	relieff__n_features_to_select	relieff__n_features_to_select: 3
*	relieff__n_jobs	relieff__n_jobs: 1
@	relieff__n_neighbors	relieff__n_neighbors: 100
*	relieff__verbose	relieff__verbose: False
@	randomforestregressor__bootstrap	randomforestregressor__bootstrap: True
@	randomforestregressor__criterion	randomforestregressor__criterion: 'mse'
@	randomforestregressor__max_depth	randomforestregressor__max_depth: None
@	randomforestregressor__max_features	randomforestregressor__max_features: 'auto'
@	randomforestregressor__max_leaf_nodes	randomforestregressor__max_leaf_nodes: None
@	randomforestregressor__min_impurity_decrease	randomforestregressor__min_impurity_decrease: 0.0
@	randomforestregressor__min_impurity_split	randomforestregressor__min_impurity_split: None
@	randomforestregressor__min_samples_leaf	randomforestregressor__min_samples_leaf: 1
@	randomforestregressor__min_samples_split	randomforestregressor__min_samples_split: 2
@	randomforestregressor__min_weight_fraction_leaf	randomforestregressor__min_weight_fraction_leaf: 0.0
@	randomforestregressor__n_estimators	randomforestregressor__n_estimators: 'warn'
*	randomforestregressor__n_jobs	randomforestregressor__n_jobs: 1
@	randomforestregressor__oob_score	randomforestregressor__oob_score: False
@	randomforestregressor__random_state	randomforestregressor__random_state: None
*	randomforestregressor__verbose	randomforestregressor__verbose: 0
@	randomforestregressor__warm_start	randomforestregressor__warm_start: False
	Note:	@, searchable params in searchcv too.