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Sebastian Schelter updated MAHOUT-1152: --------------------------------------- Component/s: (was: Integration) > mRMR feature selection algorithm > -------------------------------- > > Key: MAHOUT-1152 > URL: https://issues.apache.org/jira/browse/MAHOUT-1152 > Project: Mahout > Issue Type: Improvement > Affects Versions: 0.7 > Reporter: Claudio Reggiani > Priority: Minor > Labels: algorithm, feature > Fix For: 0.8 > > Original Estimate: 336h > Remaining Estimate: 336h > > Proposal Title: mRMR Feature Selection Algorithm on Map-Reduce. > Student Name: Claudio Reggiani > Student E-mail: nop...@gmail.com > Proposal Abstract: > The mRMR algorithm, described in [1], is a feature selection algorithm that > leverages mutual information evaluation to select features. At each > iteration, mRMR selects a new feature based on both how much it's strongly > correlated to the target output and how much it's less correlated to the > features already selected. The correlation is measured by means of mutual > information. The project proposes to provide the mRMR algorithm in MapReduce > programming framework. > Additional information: > 1. *The code is already available* with some tests, because I'm working on my > master thesis an initial milestone of my research was to implement mRMR > algorithm in MapReduce. > 2. I'm figuring out if it's possible for me to apply at Google Summer of Code > 2013. > References: > [1] Hanchuan Peng, Fuhui Long, and Chris Ding > IEEE Transactions on Pattern Analysis and Machine Intelligence, > Vol. 27, No. 8, pp.1226-1238, 2005. > Link: http://penglab.janelia.org/papersall/docpdf/2005_TPAMI_FeaSel.pdf -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira