Mercurial > repos > bgruening > keras_model_builder

annotate test-data/named_steps.txt @ 13:772e0e89fc68 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f031d8ddfb73cec24572648666ac44ee47f08aad
author bgruening
date Thu, 11 Aug 2022 08:46:52 +0000
parents ed7c222e47e3
children 624e2afa1313
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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ed7c222e47e3 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents: 0
diff changeset
1 {'preprocessing_1': SelectKBest(k=10, score_func=<function f_regression at 0x11b4ba8c8>), 'estimator': XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
ed7c222e47e3 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents: 0
diff changeset
2 colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,
ed7c222e47e3 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents: 0
diff changeset
3 max_depth=3, min_child_weight=1, missing=nan, n_estimators=100,
ed7c222e47e3 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents: 0
diff changeset
4 n_jobs=1, nthread=None, objective='reg:linear', random_state=10,
ed7c222e47e3 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents: 0
diff changeset
5 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,
ed7c222e47e3 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents: 0
diff changeset
6 silent=True, subsample=1)}