Least Square Regression for Prediction Problems in Machine Learning using R

  • Authors

    • Anila. M
    • G Pradeepini
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.17612
  • Independent variable, Dependent variable, Least square regression.

  • Abstract

    The most commonly used prediction technique is Ordinary Least Squares Regression (OLS Regression). It has been applied in many fields like statistics, finance, medicine, psychology and economics. Many people, specially Data Scientists using this technique know that it has not gone with enough training to apply it and should be checked why & when it can or can’t be applied.

    It’s not easy task to find or explain about why least square regression [1] is faced much criticism when trained and tried to apply it. In this paper, we mention firstly about fundamentals of linear regression and OLS regression along with that popularity of LS method, we present our analysis of difficulties & pitfalls that arise while OLS method is applied, finally some techniques for overcoming these problems.

     

     

  • References

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  • How to Cite

    M, A., & Pradeepini, G. (2018). Least Square Regression for Prediction Problems in Machine Learning using R. International Journal of Engineering & Technology, 7(3.12), 960-962. https://doi.org/10.14419/ijet.v7i3.12.17612

    Received date: 2018-08-16

    Accepted date: 2018-08-16

    Published date: 2018-07-20