Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Pattern classification by concurrently determined piecewise linear and convex discriminant functions
Computers and Industrial Engineering - Special issue: Computational intelligence and information technology applications to industrial engineering selected papers from the 33 rd ICC&IE
Pattern classification by concurrently determined piecewise linear and convex discriminant functions
Computers and Industrial Engineering
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Pattern classification is one of the main themes in pattern recognition,and has been tackled by several methods such as the statistic one,artificial neural networks, mathematical programming and so on. Among them,the multi-surface method proposed by Mangasarian is very attractive, becauseit can provide an exact discrimination function even for highly nonlinearproblems without any assumption on the data distribution. However, themethod often causes many slits on the discrimination curve. In other words,the piecewise linear discrimination curve is sometimes too complex resultingin a poor generalization ability. In this paper, several trials in order toovercome the difficulties of the multi-surface method are suggested. One ofthem is the utilization of goal programming in which the auxiliary linearprogramming problem is formulated as a goal programming in order to get assimple discrimination curves as possible. Another one is to apply fuzzyprogramming by which we can get fuzzy discrimination curves with gray zones.In addition, it will be shown that using the suggested methods, theadditional learning can be easily made. These features of the methods makethe discrimination more realistic. The effectiveness of the methods is shownon the basis of some applications.