An integrated model for financial data mining
|Title:||An integrated model for financial data mining||Authors:||Cai, Fan; Le-Khac, Nhien-An; Kechadi, Tahar||Permanent link:||http://hdl.handle.net/10197/10846||Date:||12-Dec-2012||Online since:||2019-07-03T08:44:16Z||Abstract:||Nowadays, financial data analysis is becoming increasingly importantin the business market. As companies collect more and more data fromdaily operations, they expect to extract useful knowledge from existing collecteddata to help make reasonable decisions for new customer requests, e.g. usercredit category, churn analysis, real estate analysis, etc. Financial institutes haveapplied different data mining techniques to enhance their business performance.However, simple approach of these techniques could raise a performance issue.Besides, there are very few general models for both understanding and forecastingdifferent financial fields. We present in this paper a new classification modelfor analyzing financial data. We also evaluate this model with different realworlddata to show its performance||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||Springer||Series/Report no.:||Lecture Notes in Computer Science; Volume 7694||Copyright (published version):||2012 Springer-Verlag Berlin Heidelberg||Keywords:||Data mining; Decision tree; Multilayer perceptron; Gaussian Process; Classification model||DOI:||10.1007/978-3-642-35455-7_28||Other versions:||https://dblp.org/db/conf/miwai/miwai2012.html||Language:||en||Status of Item:||Peer reviewed||Is part of:||Sombattheera, C., Loi, N.K., Wankar, R., Quan, T. (eds.). Multi-disciplinary Trends in Artificial Intelligence||Conference Details:||MIWAI 2012: 12th International Conference, Multi-disciplinary Trends in Artificial Intelligence, Ho Chi Minh City, Vietnam, 26-28 December 2012||ISBN:||978-3-642-35454-0|
|Appears in Collections:||Insight Research Collection|
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