Data mining in finance: From extremes to realism
Boris Kovalerchuk, Evgenii E. Vityaev · Journal of financial transformation · 2004
This paper describes data mining in finance by discussing financial tasks and specifics of methodologies and techniques in this data mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based, and relational methodologies.