view test-data/get_params05.tabular @ 0:818896cd2213 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
author bgruening
date Fri, 09 Aug 2019 07:13:13 -0400
parents
children ed7c222e47e3
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	Parameter	Value
*	memory	memory: None
*	steps	"steps: [('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=100, n_jobs=1,
           oob_score=False, random_state=42, verbose=0, warm_start=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=100, n_jobs=1,
           oob_score=False, random_state=42, verbose=0, warm_start=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: 100
*	randomforestregressor__n_jobs	randomforestregressor__n_jobs: 1
@	randomforestregressor__oob_score	randomforestregressor__oob_score: False
@	randomforestregressor__random_state	randomforestregressor__random_state: 42
*	randomforestregressor__verbose	randomforestregressor__verbose: 0
@	randomforestregressor__warm_start	randomforestregressor__warm_start: False
	Note:	@, searchable params in searchcv too.