Studying the Convergence of the CFA Algorithm
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- González J., Rojas I., Pomares H., Ortega J. (2003) Studying the Convergence of the CFA Algorithm. In: Mira J., Álvarez J.R. (eds) Computational Methods in Neural Modeling. IWANN 2003. Lecture Notes in Computer Science, vol 2686. Springer, Berlin, Heidelberg
This paper studies the convergence properties of the previously proposed CFA (Clustering for Function Approximation) algorithm and compares its behavior with other input-output clustering techniques also designed for approximation problems. The results obtained show that CFA is able to obtain an initial configuration from which an approximator can improve its performance.
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