Data mining in finance: From extremes to realism

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.

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Year of publication:	2004
Authors:	Kovalerchuk, Boris ; Vityaev, Evgenii
Published in:	Journal of Financial Transformation. - Capco Institute. - Vol. 11.2004, p. 81-89
Publisher:	Capco Institute
Subject:	Data mining \| financial services \| relational methodologies

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Type of publication:	Article
Classification:	G21 - Banks; Other Depository Institutions; Mortgages ; O33 - Technological Change: Choices and Consequences; Diffusion Processes
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008479431