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A hinge function y=h(x) consists of two hyperplanes continuously joined together at a hinge. In regression (prediction), classification (pattern recognition), and noiseless function approximation, use of sums of hinge functions gives a powerful and efficient alternative to neural networks with computation times several orders of magnitude less than is obtained by fitting neural networks with a comparable number of parameters. A simple and effective method for finding good hinges is presented.>
Leo Breiman (Sat,) studied this question.