Mercurial > repos > bgruening > sklearn_train_test_eval
annotate stacking_ensembles.py @ 3:20bb2a45f922 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
author | bgruening |
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date | Fri, 01 Nov 2019 17:12:39 -0400 |
parents | e23cfe4be9d4 |
children | ead7adad8d0e |
rev | line source |
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68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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1 import argparse |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 import ast |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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3 import json |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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4 import mlxtend.regressor |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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5 import mlxtend.classifier |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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6 import pandas as pd |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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7 import pickle |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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8 import sklearn |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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9 import sys |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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10 import warnings |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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11 from sklearn import ensemble |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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12 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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13 from galaxy_ml.utils import (load_model, get_cv, get_estimator, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
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14 get_search_params) |
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68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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15 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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16 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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17 warnings.filterwarnings('ignore') |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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18 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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19 N_JOBS = int(__import__('os').environ.get('GALAXY_SLOTS', 1)) |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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20 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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21 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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22 def main(inputs_path, output_obj, base_paths=None, meta_path=None, |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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23 outfile_params=None): |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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24 """ |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 Parameter |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 --------- |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 inputs_path : str |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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28 File path for Galaxy parameters |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 output_obj : str |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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31 File path for ensemble estimator ouput |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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32 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 base_paths : str |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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34 File path or paths concatenated by comma. |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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35 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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36 meta_path : str |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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37 File path |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 outfile_params : str |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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40 File path for params output |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 """ |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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42 with open(inputs_path, 'r') as param_handler: |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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43 params = json.load(param_handler) |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 |
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45 estimator_type = params['algo_selection']['estimator_type'] |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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46 # get base estimators |
68aaa903052a
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47 base_estimators = [] |
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48 for idx, base_file in enumerate(base_paths.split(',')): |
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49 if base_file and base_file != 'None': |
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50 with open(base_file, 'rb') as handler: |
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51 model = load_model(handler) |
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52 else: |
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53 estimator_json = (params['base_est_builder'][idx] |
68aaa903052a
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54 ['estimator_selector']) |
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55 model = get_estimator(estimator_json) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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56 |
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57 if estimator_type.startswith('sklearn'): |
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58 named = model.__class__.__name__.lower() |
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59 named = 'base_%d_%s' % (idx, named) |
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60 base_estimators.append((named, model)) |
68aaa903052a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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61 else: |
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62 base_estimators.append(model) |
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63 |
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64 # get meta estimator, if applicable |
68aaa903052a
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65 if estimator_type.startswith('mlxtend'): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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66 if meta_path: |
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67 with open(meta_path, 'rb') as f: |
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68 meta_estimator = load_model(f) |
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69 else: |
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70 estimator_json = (params['algo_selection'] |
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71 ['meta_estimator']['estimator_selector']) |
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72 meta_estimator = get_estimator(estimator_json) |
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73 |
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74 options = params['algo_selection']['options'] |
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75 |
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76 cv_selector = options.pop('cv_selector', None) |
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77 if cv_selector: |
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78 splitter, groups = get_cv(cv_selector) |
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79 options['cv'] = splitter |
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80 # set n_jobs |
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81 options['n_jobs'] = N_JOBS |
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82 |
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83 weights = options.pop('weights', None) |
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84 if weights: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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85 weights = ast.literal_eval(weights) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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86 if weights: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit eb703290e2589561ea215c84aa9f71bcfe1712c6"
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87 options['weights'] = weights |
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88 |
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89 mod_and_name = estimator_type.split('_') |
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90 mod = sys.modules[mod_and_name[0]] |
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91 klass = getattr(mod, mod_and_name[1]) |
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92 |
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93 if estimator_type.startswith('sklearn'): |
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94 options['n_jobs'] = N_JOBS |
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95 ensemble_estimator = klass(base_estimators, **options) |
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96 |
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97 elif mod == mlxtend.classifier: |
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98 ensemble_estimator = klass( |
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99 classifiers=base_estimators, |
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100 meta_classifier=meta_estimator, |
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101 **options) |
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102 |
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103 else: |
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104 ensemble_estimator = klass( |
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105 regressors=base_estimators, |
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106 meta_regressor=meta_estimator, |
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107 **options) |
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108 |
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109 print(ensemble_estimator) |
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110 for base_est in base_estimators: |
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111 print(base_est) |
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112 |
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113 with open(output_obj, 'wb') as out_handler: |
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114 pickle.dump(ensemble_estimator, out_handler, pickle.HIGHEST_PROTOCOL) |
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115 |
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116 if params['get_params'] and outfile_params: |
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117 results = get_search_params(ensemble_estimator) |
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118 df = pd.DataFrame(results, columns=['', 'Parameter', 'Value']) |
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119 df.to_csv(outfile_params, sep='\t', index=False) |
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120 |
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121 |
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122 if __name__ == '__main__': |
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123 aparser = argparse.ArgumentParser() |
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124 aparser.add_argument("-b", "--bases", dest="bases") |
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125 aparser.add_argument("-m", "--meta", dest="meta") |
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126 aparser.add_argument("-i", "--inputs", dest="inputs") |
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127 aparser.add_argument("-o", "--outfile", dest="outfile") |
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128 aparser.add_argument("-p", "--outfile_params", dest="outfile_params") |
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129 args = aparser.parse_args() |
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130 |
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131 main(args.inputs, args.outfile, base_paths=args.bases, |
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132 meta_path=args.meta, outfile_params=args.outfile_params) |