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Pattern classification using polynomial and linear regression

Author

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  • Ciuiu, Daniel

Abstract

In this paper we will classify patterns using an algorithm analogous to the k-means algorithm and the regression polynomial of the degree k (for instance, if k=1 we obtain the regression line, and if k=2 we obtain the regression parable), and the regression hyper-plane. We will also present a financial application in which we apply these regressions if the points represent the interests for accounts with different terms.

Suggested Citation

  • Ciuiu, Daniel, 2008. "Pattern classification using polynomial and linear regression," MPRA Paper 15355, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:15355
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    Citations

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    Cited by:

    1. Ciuiu, Daniel, 2008. "On Jarque-Bera normality test," Working Papers of Macroeconomic Modelling Seminar 081802, Institute for Economic Forecasting.
    2. Ciuiu, Daniel, 2010. "Modeling the fraud-like investment founds by Petri nets," MPRA Paper 23589, University Library of Munich, Germany, revised May 2010.
    3. 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.
    4. 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.

    More about this item

    Keywords

    Regression; pattern classification; k-means;
    All these keywords.

    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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