Abstract
This chapter deals with the handwritten digit recognition problem. We use a variety of classifiers for solving this problem. These classifiers include: nearest neighbour classifiers and fuzzy classifiers. A major contribution of this chapter is concerned with prototype selection for pattern classification. Genetic algorithms, simulated annealing, and tabu search are used for this purpose. The performance of various classifiers is compared based on experimental results obtained using a large data set of training and test patterns.
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