Title: Logistic regression in data analysis: an overview

Authors: Maher Maalouf

Addresses: School of Industrial Engineering, University of Oklahoma, 202 W. Boyd St., Room 124, Norman, OK, 73019, USA

Abstract: Logistic regression (LR) continues to be one of the most widely used methods in data mining in general and binary data classification in particular. This paper is focused on providing an overview of the most important aspects of LR when used in data analysis, specifically from an algorithmic and machine learning perspective and how LR can be applied to imbalanced and rare events data.

Keywords: data mining; logistic regression; data classification; rare events; imbalanced data; data analysis; machine learning.

DOI: 10.1504/IJDATS.2011.041335

International Journal of Data Analysis Techniques and Strategies, 2011 Vol.3 No.3, pp.281 - 299

Published online: 29 Nov 2014 *

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