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Outliers Detection in Regression Analysis Using Partial Least Square Approach

  • Nagaraju Devarakonda
  • Shaik Subhani
  • Shaik Althaf Hussain Basha
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 249)

Abstract

Identifying abnormal behavior in the chosen dataset is essential for improving the quality of the given dataset and decreasing the impact of abnormal values/patterns in the knowledge discovery process. Outlier detection may be established in many data mining techniques. In this paper Regression analysis have been used to detect the outliers. Partial Least Square approach is mainly used in regression analysis. Laser dataset has been used to find out the outliers. The main objective is used for constructing predictive models. The Mahalanobis distance, Jackknife distance and T2 distance were calculated for finding the outliers.

Keywords

Outliers Regression classification correlation least squares 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nagaraju Devarakonda
    • 1
  • Shaik Subhani
    • 1
  • Shaik Althaf Hussain Basha
    • 2
  1. 1.Department of Computer Science & Engg.Acharya Nagarjuna UniversityNagarjuna NagarIndia
  2. 2.Department of MCAGokaraju Rangaraju Institute of Eng. & Tech.HyderabadIndia

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