Application of several statistical classification techniques to the differentiation of whisky brands

Abstract

Abstract Several supervised (stepwise discriminant analysis (SDA), statistical isolinear multi category analysis (SIMCA) and nearest neighbour analysis (KNN)) and unsupervised (principal components analysis (PCA) and cluster analysis (CA)) classification techniques have been applied to analytical data from different whisky samples in order to distinguish between genuine whisky of a well known and expensive brand and other less expensive whiskies that could be used to replace the original contents of the bottle.