Mercurial > repos > bgruening > keras_batch_models

comparison test-data/pipeline_params18 @ 5:62b85c8ad8fa draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author bgruening
date Mon, 16 Dec 2019 05:26:20 -0500
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children 0a3f113397b2
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4:9afec58b2bf9 5:62b85c8ad8fa
1 Parameter Value
2 * memory memory: None
3 @ powertransformer powertransformer: PowerTransformer(copy=True, method='yeo-johnson', standardize=True)
4 * steps "steps: [('powertransformer', PowerTransformer(copy=True, method='yeo-johnson', standardize=True)), ('transformedtargetregressor', TransformedTargetRegressor(check_inverse=True, func=None, inverse_func=None,
5 regressor=RandomForestRegressor(bootstrap=True,
6 criterion='mse',
7 max_depth=None,
8 max_features='auto',
9 max_leaf_nodes=None,
10 min_impurity_decrease=0.0,
11 min_impurity_split=None,
12 min_samples_leaf=1,
13 min_samples_split=2,
14 min_weight_fraction_leaf=0.0,
15 n_estimators='warn',
16 n_jobs=1,
17 oob_score=False,
18 random_state=10,
19 verbose=0,
20 warm_start=False),
21 transformer=QuantileTransformer(copy=True,
22 ignore_implicit_zeros=False,
23 n_quantiles=1000,
24 output_distribution='uniform',
25 random_state=10,
26 subsample=100000)))]"
27 @ transformedtargetregressor "transformedtargetregressor: TransformedTargetRegressor(check_inverse=True, func=None, inverse_func=None,
28 regressor=RandomForestRegressor(bootstrap=True,
29 criterion='mse',
30 max_depth=None,
31 max_features='auto',
32 max_leaf_nodes=None,
33 min_impurity_decrease=0.0,
34 min_impurity_split=None,
35 min_samples_leaf=1,
36 min_samples_split=2,
37 min_weight_fraction_leaf=0.0,
38 n_estimators='warn',
39 n_jobs=1,
40 oob_score=False,
41 random_state=10,
42 verbose=0,
43 warm_start=False),
44 transformer=QuantileTransformer(copy=True,
45 ignore_implicit_zeros=False,
46 n_quantiles=1000,
47 output_distribution='uniform',
48 random_state=10,
49 subsample=100000))"
50 * verbose verbose: False
51 @ powertransformer__copy powertransformer__copy: True
52 @ powertransformer__method powertransformer__method: 'yeo-johnson'
53 @ powertransformer__standardize powertransformer__standardize: True
54 @ transformedtargetregressor__check_inverse transformedtargetregressor__check_inverse: True
55 @ transformedtargetregressor__func transformedtargetregressor__func: None
56 @ transformedtargetregressor__inverse_func transformedtargetregressor__inverse_func: None
57 @ transformedtargetregressor__regressor "transformedtargetregressor__regressor: RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,
58 max_features='auto', max_leaf_nodes=None,
59 min_impurity_decrease=0.0, min_impurity_split=None,
60 min_samples_leaf=1, min_samples_split=2,
61 min_weight_fraction_leaf=0.0, n_estimators='warn',
62 n_jobs=1, oob_score=False, random_state=10, verbose=0,
63 warm_start=False)"
64 @ transformedtargetregressor__regressor__bootstrap transformedtargetregressor__regressor__bootstrap: True
65 @ transformedtargetregressor__regressor__criterion transformedtargetregressor__regressor__criterion: 'mse'
66 @ transformedtargetregressor__regressor__max_depth transformedtargetregressor__regressor__max_depth: None
67 @ transformedtargetregressor__regressor__max_features transformedtargetregressor__regressor__max_features: 'auto'
68 @ transformedtargetregressor__regressor__max_leaf_nodes transformedtargetregressor__regressor__max_leaf_nodes: None
69 @ transformedtargetregressor__regressor__min_impurity_decrease transformedtargetregressor__regressor__min_impurity_decrease: 0.0
70 @ transformedtargetregressor__regressor__min_impurity_split transformedtargetregressor__regressor__min_impurity_split: None
71 @ transformedtargetregressor__regressor__min_samples_leaf transformedtargetregressor__regressor__min_samples_leaf: 1
72 @ transformedtargetregressor__regressor__min_samples_split transformedtargetregressor__regressor__min_samples_split: 2
73 @ transformedtargetregressor__regressor__min_weight_fraction_leaf transformedtargetregressor__regressor__min_weight_fraction_leaf: 0.0
74 @ transformedtargetregressor__regressor__n_estimators transformedtargetregressor__regressor__n_estimators: 'warn'
75 * transformedtargetregressor__regressor__n_jobs transformedtargetregressor__regressor__n_jobs: 1
76 @ transformedtargetregressor__regressor__oob_score transformedtargetregressor__regressor__oob_score: False
77 @ transformedtargetregressor__regressor__random_state transformedtargetregressor__regressor__random_state: 10
78 * transformedtargetregressor__regressor__verbose transformedtargetregressor__regressor__verbose: 0
79 @ transformedtargetregressor__regressor__warm_start transformedtargetregressor__regressor__warm_start: False
80 @ transformedtargetregressor__transformer "transformedtargetregressor__transformer: QuantileTransformer(copy=True, ignore_implicit_zeros=False, n_quantiles=1000,
81 output_distribution='uniform', random_state=10,
82 subsample=100000)"
83 @ transformedtargetregressor__transformer__copy transformedtargetregressor__transformer__copy: True
84 @ transformedtargetregressor__transformer__ignore_implicit_zeros transformedtargetregressor__transformer__ignore_implicit_zeros: False
85 @ transformedtargetregressor__transformer__n_quantiles transformedtargetregressor__transformer__n_quantiles: 1000
86 @ transformedtargetregressor__transformer__output_distribution transformedtargetregressor__transformer__output_distribution: 'uniform'
87 @ transformedtargetregressor__transformer__random_state transformedtargetregressor__transformer__random_state: 10
88 @ transformedtargetregressor__transformer__subsample transformedtargetregressor__transformer__subsample: 100000
89 Note: @, params eligible for search in searchcv tool.