Feature Selection - Data Mining with Decision Trees: Theory and Applications - page 223

encounter the aforementioned diculties derived from a high number of
instances.
Practically, most of the training sets are still considered “small” not
because of their absolute size but rather due to the fact that they contain
too few instances given the nature of the investigated problem, namely
the instance space size, the space distribution and the intrinsic noise.
Furthermore, even if a sucient dataset is available, the researcher will
probably encounter the aforementioned di culties derived from a high
number of records.