Indicator bacteria at five swimming beaches*analysis using random forests

["Shannon Briggs" <briggssl@michigan.gov>]

Water Research 
Volume 39, Issue 7, April 2005, Pages 1354-1360  

Indicator bacteria at five swimming beaches*analysis using random forests 

David F. Parkhurst, Kristen P. Brenner, Alfred P. Dufour and Larry J. Wymer 

Environmental Science Research Center, School of Public and Environmental Affairs, Indiana University, 1315 East Tenth Street, Bloomington, IN 47405-1701, USA
National Exposure Research Laboratory, US Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA 

Received 15 July 2004;  revised 27 December 2004;  accepted 3 January 2005.  Available online 8 February 2005. 

Abstract
"Random forests," an extension of tree regression, provide a relatively new technique for exploring relationships of a response variable like the density of indicator bacteria in water to numerous potential explanatory variables. We used this tool to study relationships of indicator density at five beaches to numerous other variables and found that day of the week, indicator density 24 h earlier, water depth at the sampling point, cloud cover, and others were related to density at one or more of the beaches. Using data from the first 52 days of measurement allowed predicting indicator densities in the following 10 days to order of magnitude at some of the beaches. Our analyses served to demonstrate the potential usefulness of this analytic tool for large data sets with many variables. 

Keywords: Random forests; Tree regression; Swimming beaches; Indicator bacteria 

Corresponding author. Tel.: +1 812 855 4556; fax: +1 812 855 7802. 

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