annotate test-data/get_params04.tabular @ 4:aff86cee673c draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
author bgruening
date Tue, 13 Apr 2021 22:48:19 +0000
parents 13226b2ddfb4
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13226b2ddfb4 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
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1 Parameter Value
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2 * memory memory: None
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3 * steps "steps: [('selectfrommodel', SelectFromModel(estimator=AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None,
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4 learning_rate=1.0, n_estimators=50, random_state=None),
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5 max_features=None, norm_order=1, prefit=False, threshold=None)), ('linearsvc', LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,
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6 intercept_scaling=1, loss='squared_hinge', max_iter=1000,
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7 multi_class='ovr', penalty='l2', random_state=None, tol=0.0001,
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8 verbose=0))]"
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9 @ selectfrommodel "selectfrommodel: SelectFromModel(estimator=AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None,
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10 learning_rate=1.0, n_estimators=50, random_state=None),
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11 max_features=None, norm_order=1, prefit=False, threshold=None)"
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12 @ linearsvc "linearsvc: LinearSVC(C=1.0, class_weight=None, dual=True, fit_intercept=True,
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13 intercept_scaling=1, loss='squared_hinge', max_iter=1000,
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14 multi_class='ovr', penalty='l2', random_state=None, tol=0.0001,
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15 verbose=0)"
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16 @ selectfrommodel__estimator__algorithm selectfrommodel__estimator__algorithm: 'SAMME.R'
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17 @ selectfrommodel__estimator__base_estimator selectfrommodel__estimator__base_estimator: None
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18 @ selectfrommodel__estimator__learning_rate selectfrommodel__estimator__learning_rate: 1.0
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19 @ selectfrommodel__estimator__n_estimators selectfrommodel__estimator__n_estimators: 50
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20 @ selectfrommodel__estimator__random_state selectfrommodel__estimator__random_state: None
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21 @ selectfrommodel__estimator "selectfrommodel__estimator: AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None,
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22 learning_rate=1.0, n_estimators=50, random_state=None)"
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23 @ selectfrommodel__max_features selectfrommodel__max_features: None
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24 @ selectfrommodel__norm_order selectfrommodel__norm_order: 1
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25 @ selectfrommodel__prefit selectfrommodel__prefit: False
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26 @ selectfrommodel__threshold selectfrommodel__threshold: None
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27 @ linearsvc__C linearsvc__C: 1.0
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28 @ linearsvc__class_weight linearsvc__class_weight: None
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29 @ linearsvc__dual linearsvc__dual: True
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30 @ linearsvc__fit_intercept linearsvc__fit_intercept: True
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31 @ linearsvc__intercept_scaling linearsvc__intercept_scaling: 1
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32 @ linearsvc__loss linearsvc__loss: 'squared_hinge'
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33 @ linearsvc__max_iter linearsvc__max_iter: 1000
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34 @ linearsvc__multi_class linearsvc__multi_class: 'ovr'
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35 @ linearsvc__penalty linearsvc__penalty: 'l2'
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36 @ linearsvc__random_state linearsvc__random_state: None
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37 @ linearsvc__tol linearsvc__tol: 0.0001
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38 * linearsvc__verbose linearsvc__verbose: 0
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39 Note: @, searchable params in searchcv too.