An integrated model for financial data mining

Files in This Item:
File Description SizeFormat 
insight_publication.pdf283.66 kBAdobe PDFDownload
Title: An integrated model for financial data mining
Authors: Cai, FanLe-Khac, Nhien-AnKechadi, 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 miningDecision treeMultilayer perceptronGaussian ProcessClassification 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

Show full item record

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.