Use and misuse of supervised pattern recognition methods for interpreting compositional data.
In this paper, the critical aspects of supervised learning pattern recognition techniques are examined in order to apply the suitable methodology avoiding its abuse and misuse that could provide pitfalls and misleading results.
González
A Gustavo
AG
Department of Analytical Chemistry, University of Seville, C/Profesor Garcia González no 1, 41012 Seville, Spain. agonzale@us.es
D010363:Pattern Recognition, Automated