We answer two open questions concerning the existence of universal schemes
for classification and regression estimation from stationary ergodic proces
ses. It is shown that no measurable procedure can produce weakly consistent
regression estimates from every bivariate stationary ergodic process, even
if the covariate and response variables are restricted to take values in t
he unit interval. It is further shown that no measurable procedure can prod
uce weakly consistent 'classification rules from every bivariate stationary
ergodic process for which the response variable is binary valued. The resu
lts of the paper are derived via reduction arguments and are based in part
on recent work concerning density estimaton from ergodic processes.