Evaluating the accuracy of classification methods for rating wines based on their physical and chemical characteristics
is an important part of the wine industry. An ability to accurately predict the quality of wine based on this information
provides vast opportunity for applications in other areas of science. Recently, a method was proposed that utilises
data mining techniques for the prediction of the quality of wines based solely on their physicochemical properties and
compared these results with those classifications obtained by experienced assessors. In this paper we explore an analytical
approach to evaluating the accuracy of these classification methods using new advances in the area of statistical modelling.
Keywords: Classification methods, Confusion Matrix, Estimation methods, Ordinal log-linear models, Physicochemical characteristics,
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