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Activity Number: 356
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #303998
Title: The RSpec Package: Raman Spectra Pre-Processing and Classification in R
Author(s): Qi Wang*+ and Dianne H Cook and Chenxu Yu
Companies: Iowa State University and Iowa State University and Iowa State University
Address: 3155 NSRIC, Ames, IA, 50010, United States
Keywords: spectral pre-processing ; R package ; support vector machine ; artificial neutral network ; random forest ; partial least squares regression

The "RSpec" package implements basic and classical Raman spectral pre-processing methods for raw spectra in R, such as polynomial baseline correction, maximum intensity normalization, area normalization, specific peak normalization, moving average points smoothing, first and second derivative spectra calculation, binary spectra calculation. In addition, classification and regression methods support vector machine, artificial neutral network, random forest and partial least squares regression are included in "RSpec" for further data analysis. Two example sections about "Glaucoma" and "Beef Sensory" are provided for demonstrating. "RSpec" will be freely available from the Comprehensive R Archive Network (CRAN), licensed under the GNU General Public License (GPL).

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