Discriminant analysis is used in situations where the clusters are known a priori. The aim of discriminant analysis is to classify an observation, or several observations, into these known groups. For instance, in credit scoring, a bank knows from past experience that there are good customers (who repay their loan without any problems) and bad customers (who have had difficulties repaying their loans). When a new customer asks for a loan, the bank has to decide whether or not to give the loan. The information of the bank is given in two data sets: multivariate observations on the two categories of customers (including age, salary, marital status, the amount of the loan, and the like).
KeywordsDiscriminant Analysis Point Cloud Prior Probability Bank Note Fisher Linear Discriminant
Unable to display preview. Download preview PDF.