Business intelligence for predicting consumer price index | |
| Author | Bonneton, Bastien |
| Call Number | AIT RSPR no.ICT-10-14 |
| Subject(s) | Business intelligence--Data processing Consumer price index |
| Note | A research study submitted in partial fulfilment of the requirements for the degree of Master of Engineering in Information and Communication Technologies, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no. ICT-10-14 |
| Abstract | Business Intelligence (BI), more precisely data mining, and macro-economical indicator, namely Consumer Price Index (CPI), have not been much integrated as they should be. Data mining techniques provide some powerful tools to get insight on future trends of financial indicators. This study suggests applying different data mining techniques (Regression, Decision Tree and Neural Network) to a dataset composed of CPI predictors in order to forecast the value of this economical indicator. To achieve this Weka open source software was to provide all kinds of prediction tools. The study gives conclusions on the best type of data and the best BI model to use in order to perform the most accurate prediction. The best BI model to predict CPI is Neural Network, with the smallest error rates. |
| Year | 2010 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no. ICT-10-14 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information and Communication Technology (ICT) |
| Chairperson(s) | Vatcharaporn Esichaikul; |
| Examination Committee(s) | Janecek, Paul;Guha, Sumanta ; |
| Scholarship Donor(s) | Telecom SudParis;Asian Institute of Technology Fellowship; |
| Degree | Research Studies Project Report (M.Eng.) - Asian Institute of Technology, 2010 |