Almost everywhere convergence of a recursive regression function estimate and classification (Corresp.)

It is shown that the recursive kernel estimate of the regression functionE(Y|X = x)is consistent at almost everyx(\mu)regardless of the distribution\muofX. Thus the result is distribution-free. From this we show that the risk for a suitable classification rule derived from the estimate converges to Bayes´ risk, no matter what the class distributions are.