DATA MINING BASED MODEL AGGREGATION

Applying modelling techniques for getting acquainted with customer behaviour, predicting the customers’ next step is neccessary to keep in competition, by decreasing the capital requirement (Basel II - IRB) or making the portfolio more profitable. According to the easily implementable modelling techniques, data mining solutions widespread in practice. Using these models with no conditions can lead into inconsistent future on portfolio change. Consequence of this situation, contradictory predictions and conclusions come into existence. Recognizing and conscious handling of inconsistent predictions is an important task for experts working on different scene of the knowledge based economy and society. By realizing and solving the problem of inconsistency in modelling processes, the competitive advantage can be increased and strategic decisions can be supported by consistent predictions.


Issue Date:
2007
Publication Type:
Journal Article
DOI and Other Identifiers:
10.22004/ag.econ.58928
ISSN 0046-5518 (Other)
Record Identifier:
https://ageconsearch.umn.edu/record/58928
PURL Identifier:
http://purl.umn.edu/58928
Published in:
GAZDÁLKODÁS: Scientific Journal on Agricultural Economics, 51, Special Edition 19
Page range:
222-230
Total Pages:
9
Series Statement:
51.
19. Special Issue




 Record created 2017-04-01, last modified 2019-08-26

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