Logistic regression in data analysis: an overview Online publication date: Sat, 16-Jul-2011
by Maher Maalouf
International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 3, No. 3, 2011
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.
Online publication date: Sat, 16-Jul-2011
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Analysis Techniques and Strategies (IJDATS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.If you still need assistance, please email firstname.lastname@example.org