Mercurial > pylearn
comparison doc/v2_planning/architecture.txt @ 1190:9ff2242a817b
fix rst syntax errors/warnings
author | Frederic Bastien <nouiz@nouiz.org> |
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date | Fri, 17 Sep 2010 21:14:41 -0400 |
parents | f111f8c2a280 |
children | 46527ae6db53 |
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1189:0e12ea6ba661 | 1190:9ff2242a817b |
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74 don't. I do find, however, some not-so-deep-but-still-significant advantages | 74 don't. I do find, however, some not-so-deep-but-still-significant advantages |
75 to the linear version, which hopefully can be made clear (along with a | 75 to the linear version, which hopefully can be made clear (along with a |
76 clarification of what the h*** am I talking about) in the following example: | 76 clarification of what the h*** am I talking about) in the following example: |
77 | 77 |
78 * Linear version: | 78 * Linear version: |
79 | |
80 .. code-block:: python | |
81 | |
79 my_experiment = pipeline([ | 82 my_experiment = pipeline([ |
80 data, | 83 data, |
81 filter_samples, | 84 filter_samples, |
82 PCA, | 85 PCA, |
83 k_fold_split, | 86 k_fold_split, |
84 neural_net, | 87 neural_net, |
85 evaluation, | 88 evaluation, |
86 ]) | 89 ]) |
87 | 90 |
88 * Encapsulated version: | 91 * Encapsulated version: |
92 | |
93 .. code-block:: python | |
94 | |
89 my_experiment = evaluation( | 95 my_experiment = evaluation( |
90 data=PCA(filter_samples(data)), | 96 data=PCA(filter_samples(data)), |
91 split=k_fold_split, | 97 split=k_fold_split, |
92 model=neural_net) | 98 model=neural_net) |
93 | 99 |