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Pattern Classification Using Secondary Components Perceptron and Economic Applications

Author

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  • Ciuiu, Daniel

    (Technical University of Civil Engineering, Bucharest, Romania)

Abstract

In this paper we will classify patterns using a modified Perceptron algorithm (Dumitrache et al., 1999). The generalization uses the eigenvalues and the eigenvectors of the sample covariance matrix, as we did for classifying patterns using PCR (Ciuiu 2007b).We shall also define measurements for the cohesion of the obtained classes and of the separation between them. The first economic application considered in the paper is a consumer behavior model (Jula 2003), and the second is the same financial application for classifying banks (Ciuiu, 2007a, Ciuiu, 2007b), where we have used regression for classification.

Suggested Citation

  • 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.
    • Handle: RePEc:rjr:romjef:v:5:y:2008:i:2:p:51-66
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    References listed on IDEAS

    as
    1. Ciuiu, Daniel, 2008. "Pattern classification using polynomial and linear regression," MPRA Paper 15355, University Library of Munich, Germany.
    2. Ciuiu, Daniel & Costinescu, Cristian, 2008. "The Monte Carlo method to find eigenvalues and eigenvectors," MPRA Paper 15362, University Library of Munich, Germany.
    3. Nastac, Iulian & Dobrescu, Emilian & Pelinescu, Elena, 2007. "Neuro-Adaptive Model for Financial Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(3), pages 19-41, September.
    4. Ciuiu, Daniel, 2008. "Pattern classification using principal components regression," MPRA Paper 15360, University Library of Munich, Germany.
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    Citations

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    Cited by:

    1. 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.
    2. 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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    More about this item

    Keywords

    Perceptron; principal and secondary components; consumption; banks;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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