Difference between revisions of "GSoC2013 Coding Challenge"

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== Implementing Machine Learning Algorithms for Classification and Feature Selection in Mothur ==
 
== Implementing Machine Learning Algorithms for Classification and Feature Selection in Mothur ==
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* Using any open source tools i.e. R, Octave, scikit-learn, libsvm, shogun ML toolbox etc and scripting, run any one of the feature selection algorithms on the data provided
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* Write a prototype implementation of svm or enet and try it on the data provided
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The output should be in the following format. The rank is a relative term, not an absolute value. It denotes the relative importance between the features.
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OTU    Rank
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Otu0022    5.55
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Otu0077    0.93
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Otu0840    0.82
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Otu0299    0.8
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Otu0170    0.79
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Otu0566    0.78
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Otu0372    0.78
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Otu0365    0.77

Revision as of 01:39, 5 May 2013

Implementing Machine Learning Algorithms for Classification and Feature Selection in Mothur

  • Using any open source tools i.e. R, Octave, scikit-learn, libsvm, shogun ML toolbox etc and scripting, run any one of the feature selection algorithms on the data provided
  • Write a prototype implementation of svm or enet and try it on the data provided

The output should be in the following format. The rank is a relative term, not an absolute value. It denotes the relative importance between the features.

OTU Rank Otu0022 5.55 Otu0077 0.93 Otu0840 0.82 Otu0299 0.8 Otu0170 0.79 Otu0566 0.78 Otu0372 0.78 Otu0365 0.77