Least squares regression vs. geometric mean regression for ecotoxicology studies
Applied Mathematics and Computation
Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
A new approach for classification: visual simulation point of view
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
ϵ-insensitive fuzzy c-regression models: introduction to ϵ-insensitive fuzzy modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid neural network model for noisy data regression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The regression is one of the fundamental problems in data mining, which is central to many applications of information technology. Various approaches have been presented for regression problem nowadays. However, many problems still exist, such as efficiency and model selection problem. This paper proposes a new approach to regression problem, visual regression problem (VRA) in order to resolve these problems. The core idea is to transfer the regression problem to classification problem based on Ancona theorem, which gives the mathematical equivalence between two problems; and then use visual classification approach, which is an efficient classification approach developed based on mimicking human sensation and perception principle, to solve the transformed classification problem and get an implicit regression function; and finally utilize some mathematical skills to obtain the explicit solution of the regression problem. We also provide a series of simulations to demonstrate that the proposed approach is not only effective but also efficient.