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The certainty factor-based neural network in continuous classification domains

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1 Author(s)
Limin Fu ; Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA

The integration of certainty factors (CFs) into the neural computing framework has resulted in a special artificial neural network known as the CFNet. This paper presents the cont-CFNet, which is devoted to classification domains where instances are described by continuous attributes. A new mathematical analysis on learning behavior, specifically linear versus nonlinear learning, is provided that can serve to explain how the cont-CFNet discovers patterns and estimates output probabilities. Its advantages in performance and speed have been demonstrated in empirical studies

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Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:30 ,  Issue: 4 )