A comparison of model-based and regression classification techniques applied to near infrared spectroscopic data in food authentication studies

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Optimization of FTIR-ATR spectroscopy for botanical authentication of unifloral honey types and melissopalynological data prediction (2015, background): “Since statistical models with large number of latent variables are not commonly accepted in current practice due to the concern of possible overfitting [51], it can be assumed that a big number of latent variables (>25) in case of IR spectroscopic analysis of honey leads to perplexity of the statist”
Model-based Methods of Classification: Using the mclust Software in Chemometrics (2007, background): “... Fraley, Raftery, and Wehrens 2005; Tran, Wehrens, and Buydens 2006), magnetic resonance imaging (Wehrens et al. 2002; Fraley et al. 2005; Forbes, Peyrard, Fraley, Georgian-Smith, Goldhaber, and Raftery 2006), microarray image segmentation (Li, Fraley, Bumgarner, Yeung, and Raftery 2005; Fraley a”