  In a previous letter, we studied learning from stochastic examples by
perceptrons with Ising weights in the framework of statistical mechanics. Under
the one-step replica symmetry breaking ansatz, the behaviours of learning
curves were classified according to some local property of the rules by which
examples were drawn. Further, the conditions for the existence of the Perfect
Learning together with other behaviors of the learning curves were given. In
this paper, we give the detailed derivation about these results and further
argument about the Perfect Learning together with extensive numerical
calculations.
