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Multi-surface method : ウィキペディア英語版 | Multi-surface method The multi-surface method (MSM) is a form of decision making using the concept of piecewise-linear separability of datasets to categorize data. ==Introduction== Two datasets are linearly separable if their convex hulls do not intersect. The method may be formulated as a feedforward neural network with weights that are trained via linear programming. Comparisons between neural networks trained with the MSM versus backpropagation show MSM is better able to classify data.〔''(Neural Network Training via Linear Programing )'', Advances in Optimization and Parallel Computing, 1992, p. 56〕 The decision problem associated linear program for the MSM is NP-Complete.
抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Multi-surface method」の詳細全文を読む
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