meatspec

A Tecator Infratec Food and Feed Analyzer working
  in the wavelength
range 850 - 1050 nm by the Near Infrared Transmission (NIT) principle
was used to collect data on samples of finely chopped pure meat. 215
samples were measured. For each sample, the fat content was measured
along with a 100 channel spectrum of absorbances. Since determining
the fat content via analytical chemistry is time consuming we would
like to build a model to predict the fat content of new samples using
the 100 absorbances which can be measured more easily.


datasets

Engines for cross-validation of many types of regression and class prediction models are provided. These engines include built-in support for 'glmnet', 'lars', 'plus', 'MASS', 'rpart', 'C50' and 'randomforest'. It is easy for the user to add other regression or classification algorithms. The 'parallel' package is used to improve speed. Several data generation algorithms for problems in regression and classification are provided.

A.I. McLeod

gencve

General Cross Validation Engine

meatspec function

Dataset contains the following variables
  <dl>
    <dt><code>V1-V100</code></dt><dd> absorbances across a range of 100 wavelengths
    </dd> <dt><code>fat</code></dt><dd> fat content</dd> </dl> 

Format

This data was used in Faraway's book on Regression and his R
package. He cites the following:
H. H. Thodberg (1993) "Ace of Bayes: Application of Neural
  Networks With Pruning", report no. 1132E, Maglegaardvej 2,
  DK-4000 Roskilde, Danmark

meatspec: Meat Spectrometry to Determine Fat Content

Description

Usage

Arguments

Format

Source