Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Comparative Analysis of Outlier Detection Methods

Author : Mahvish Fatima 1 Jitendra Kurmi 2

Date of Publication :30th April 2018

Abstract: This paper presents different types of outlier detection methods. There are many factors which generate outliers it can be a measurement error, instrumentation error etc. No matter whatever is the reason outliers can be identified using these methods effectively. The experiment was conducted on SPSS tool. The comparative analysis of these methods was performed successfully. The aim of this paper was to analyze the methods of outlier detection from the research point of view. Furthermore, we find out the impact of different methods on the dataset containing outliers.

Reference :

    1. Christophe Leys, Christophe Ley, Olivier Klein, Philippe Bernard, Laurent Licata J. U. Duncombe, “Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median,” Elsevier YJESP-03038; No. of pages: 3; 4C, March 10, 2013
    2. Girish Kumar Sharma, Promila Sharma, “A Study on Data Mining algorithms for Tourism Industry,” ILJET, vol. 7, issue 1, May 2016.
    3. George Kurian, Hongmei Chi, “Predict Florida Tourism Trend via Using Data Mining Techniques,” PEARC17, New Orleans, LA, USA, July 09-13, 2017.

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