Hypothetico-deductive data mining
David McSherry · Applied Stochastic Models and Data Analysis · 1997
An algorithm for rule discovery in databases is described which is based on the reasoning strategies of human diagnosticians. It differs from other algorithms in its hypothesis-driven approach and primarily qualitative assessment of rule interest. Upper and lower bounds are established for the value of a quantitative measure used in the algorithm to rank rules of equal qualitative interest. An example based on consumer choices is used to illustrate the rule discovery process. © 1998 John Wiley & Sons, Ltd.