IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/15355.html
   My bibliography  Save this paper

Pattern classification using polynomial and linear regression

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/15355/1/MPRA_paper_15355.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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, 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.
    3. Ciuiu, Daniel, 2010. "Modeling the fraud-like investment founds by Petri nets," MPRA Paper 23589, University Library of Munich, Germany, revised May 2010.
    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:15355. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.