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On 16:56 Mon 21 Mar , Brian Dolbec wrote: |
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> There is an app called shogun-toolbox http://www.shogun-toolbox.org/ |
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> |
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> that is designed specifically for machine learning. It has many |
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> interface capabilities including python (which they state has the most |
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> complete documentation). There is also many examples for it's use. |
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> |
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> I personally don't know nearly enough about it to know what modeling |
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> methods might be suitable or even if there is one suitable for this |
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> type of model. But I think should be investigated. Implemented this |
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> would have the potential to increase it's success rate over time, |
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> reducing developer load even more. |
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This sounds like something that might be beyond a GSoC project to |
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develop a standalone code base. It would probably work better next year |
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as an enhancement, if this year's project to build an initial working |
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application worked out well. |
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What I would do instead is a "smart" detection using things like |
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flex/bison/pybison. You could first detect the buildsystem type |
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(autotools/cmake/distutils/etc) based on file existence. Then you would |
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parse the build files using the syntax described for your lexical |
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analyzer/parser to build a basic understanding of what build-time |
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options are available and offer them as USE flags. You could also do |
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similar things to detect dependencies by understanding their syntax in |
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the source code. |
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|
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-- |
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Thanks, |
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Donnie |
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|
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Donnie Berkholz |
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Admin, Summer of Code |
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Gentoo Linux |
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Blog: http://dberkholz.com |
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