Pattern classification using principal components regression
AbstractIn this paper we will classify patterns using an algorithm analogous to the k-means algorithm and the principal components regression (PCR). We will also present a financial application in which we apply PCR if the points represent the interests for accounts with different terms.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 15360.
Date of creation: Jan 2008
Date of revision:
Principal components regression; pattern classification; k-means;
Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Albu, Lucian-Liviu & Ciuiu, Daniel, 2009. "A method to evaluate composite performance indices based on variance-covariance matrix," MPRA Paper 19979, University Library of Munich, Germany, revised Aug 2009.
- Ciuiu, Daniel, 2008. "Pattern Classification Using Secondary Components Perceptron and Economic Applications," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(2), pages 51-66, June.
- Ciuiu, Daniel, 2010. "Informational Criteria for the Homoscedasticity of Errors," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 231-244, July.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.