The importance of example set quality in induction

Inductive algorithms start from a set of examples of a solved problem and generate rules which classify the solutions to the problem in terms of attributes describing the problem. Inductive methods are not necessarily easy to apply, and success is likely to depend on the quality of the example set in the chosen domain. Recognition before acquisition of the likelihood of obtaining a good quality example set would clearly be desirable, and some parameters leading towards such recognition have been identified