Mercurial > repos > bgruening > sklearn_nn_classifier

comparison test-data/get_params02.tabular @ 10:e9ba818e7877 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
author bgruening
date Tue, 14 May 2019 18:09:43 -0400
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9:ed7b1654e841 10:e9ba818e7877
1 Parameter Value
2 * memory memory: None
3 * steps "steps: [('robustscaler', RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
4 with_scaling=True)), ('lassocv', LassoCV(alphas=None, copy_X=True, cv='warn', eps=0.001, fit_intercept=True,
5 max_iter=1000, n_alphas=100, n_jobs=1, normalize=False, positive=False,
6 precompute='auto', random_state=None, selection='cyclic', tol=0.0001,
7 verbose=False))]"
8 @ robustscaler "robustscaler: RobustScaler(copy=True, quantile_range=(25.0, 75.0), with_centering=True,
9 with_scaling=True)"
10 @ lassocv "lassocv: LassoCV(alphas=None, copy_X=True, cv='warn', eps=0.001, fit_intercept=True,
11 max_iter=1000, n_alphas=100, n_jobs=1, normalize=False, positive=False,
12 precompute='auto', random_state=None, selection='cyclic', tol=0.0001,
13 verbose=False)"
14 @ robustscaler__copy robustscaler__copy: True
15 @ robustscaler__quantile_range robustscaler__quantile_range: (25.0, 75.0)
16 @ robustscaler__with_centering robustscaler__with_centering: True
17 @ robustscaler__with_scaling robustscaler__with_scaling: True
18 @ lassocv__alphas lassocv__alphas: None
19 @ lassocv__copy_X lassocv__copy_X: True
20 @ lassocv__cv lassocv__cv: 'warn'
21 @ lassocv__eps lassocv__eps: 0.001
22 @ lassocv__fit_intercept lassocv__fit_intercept: True
23 @ lassocv__max_iter lassocv__max_iter: 1000
24 @ lassocv__n_alphas lassocv__n_alphas: 100
25 * lassocv__n_jobs lassocv__n_jobs: 1
26 @ lassocv__normalize lassocv__normalize: False
27 @ lassocv__positive lassocv__positive: False
28 @ lassocv__precompute lassocv__precompute: 'auto'
29 @ lassocv__random_state lassocv__random_state: None
30 @ lassocv__selection lassocv__selection: 'cyclic'
31 @ lassocv__tol lassocv__tol: 0.0001
32 * lassocv__verbose lassocv__verbose: False
33 Note: @, searchable params in searchcv too.