Abstract
We study in detail the behavior of some known learning algorithms. We estimate the sum of the squares of the absolute relative errors of some general linear learning algorithms and the sum of the squares of the coefficients obtained by the perceptron algorithm. We prove the convergence of a statistical learning algorithm. The possibility of applications of this theory to biology is discussed.
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