On the Hermite Series-Based Generalized Regression Neural Networks for Stream Data Mining
Abstract: In the paper, we develop the mathematically justified stream data mining algorithm for solving regression problems. The algorithm is based on the Hermite expansions of drifting regression functions. The global convergence, in the \(L_2\) space, is proved both in probability and with probability one. The examples of several concept drifts to be handled by our algorithm, and the illustrative simulations are presented.
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