Codes for the BigLS Workshop (2014)
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README.md

About

This repository contains the scripts and IPython notebooks that can be used to reproduce the results by Ditzler and Rosen (2014). The work focuses on things to consider when examining feature subset selection when applied to abundance data in the microbiome. Our goal in this work is to examine the role, assumptions, and inferences that feature subset selection can provide the field of microbial ecology and comparative metagenomics. Specifically we examine feature subset selection algorithms using embedded and filter approaches to infer taxa importance on data collected from the human gut microbiome.

The code in this repository is licensed under the GNU GPL v3.

Dependencies

Citation Policy

If you the scripts scripts in this work, and you plan to publish a manuscript based on these codes, please add the following citation:

  • Gregory Ditzler and Gail Rosen, ``Feature Subset Selection for Inferring Relative Importance of Taxonomy,'' to appear ACM International Workshop on Big Data in Life Sciences, 2014.