Logistic regression in data analysis: an overview. (1st January 2011)

• Record Type: Journal Article
• Authors: Maalouf, Maher
• Is Part Of: International journal of data analysis techniques and strategies. Volume 3:Number 3(2011)
• Page Start: 281
• Page End: 299
• Publication Date: 2011-01-01
• Subjects: data mining -- logistic regression -- LR -- classification -- rare events -- imbalanced data; Electronic data processing -- Periodicals; Database searching -- Periodicals; 005
• Languages: English
• ISSNs: 1755-8050

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.