Abstract
The main groups of classifiers including twoclass, oneclass, and multiclass classifiers are described including Euclidean distance to centroids, linear discriminant analysis, quadratic discriminant analysis, partial least squares discriminant analysis, support vector machines, support vector domain description and Soft Independent Modeling of Class Analogy (SIMCA) amongst others. The importance of validation to obtain meaningful assessments of classifiers and the difference with optimization are discussed. The problems of obtaining misleading and overoptimistic results are described.
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