view test-data/get_params03.tabular @ 8:913ee94945f3 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
author bgruening
date Tue, 14 May 2019 18:06:37 -0400 (2019-05-14)
parents
children
line wrap: on
line source
	Parameter	Value
*	memory	memory: None
*	steps	"steps: [('robustscaler', RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
       with_scaling=True)), ('xgbclassifier', XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
       colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
       max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
       n_jobs=1, nthread=None, objective='binary:logistic', random_state=0,
       reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
       silent=True, subsample=1))]"
@	robustscaler	"robustscaler: RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
       with_scaling=True)"
@	xgbclassifier	"xgbclassifier: XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
       colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
       max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
       n_jobs=1, nthread=None, objective='binary:logistic', random_state=0,
       reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
       silent=True, subsample=1)"
@	robustscaler__copy	robustscaler__copy: True
@	robustscaler__quantile_range	robustscaler__quantile_range: (25.0, 75.0)
@	robustscaler__with_centering	robustscaler__with_centering: True
@	robustscaler__with_scaling	robustscaler__with_scaling: True
@	xgbclassifier__base_score	xgbclassifier__base_score: 0.5
@	xgbclassifier__booster	xgbclassifier__booster: 'gbtree'
@	xgbclassifier__colsample_bylevel	xgbclassifier__colsample_bylevel: 1
@	xgbclassifier__colsample_bytree	xgbclassifier__colsample_bytree: 1
@	xgbclassifier__gamma	xgbclassifier__gamma: 0
@	xgbclassifier__learning_rate	xgbclassifier__learning_rate: 0.1
@	xgbclassifier__max_delta_step	xgbclassifier__max_delta_step: 0
@	xgbclassifier__max_depth	xgbclassifier__max_depth: 3
@	xgbclassifier__min_child_weight	xgbclassifier__min_child_weight: 1
@	xgbclassifier__missing	xgbclassifier__missing: nan
@	xgbclassifier__n_estimators	xgbclassifier__n_estimators: 100
*	xgbclassifier__n_jobs	xgbclassifier__n_jobs: 1
*	xgbclassifier__nthread	xgbclassifier__nthread: None
@	xgbclassifier__objective	xgbclassifier__objective: 'binary:logistic'
@	xgbclassifier__random_state	xgbclassifier__random_state: 0
@	xgbclassifier__reg_alpha	xgbclassifier__reg_alpha: 0
@	xgbclassifier__reg_lambda	xgbclassifier__reg_lambda: 1
@	xgbclassifier__scale_pos_weight	xgbclassifier__scale_pos_weight: 1
@	xgbclassifier__seed	xgbclassifier__seed: None
@	xgbclassifier__silent	xgbclassifier__silent: True
@	xgbclassifier__subsample	xgbclassifier__subsample: 1
	Note:	@, searchable params in searchcv too.