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.
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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
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- 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.
- 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, 2010. "Informational Criteria for the Homoscedasticity of Errors," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 231-244, July.
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