Logistic regression in large rare events and imbalanced data: A performance comparison of prior correction and weighting methods-Reference-Cited by-同舟云学术

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Logistic regression in large rare events and imbalanced data: A performance comparison of prior correction and weighting methods

Published:2017-08-09 Issue:1 Volume:34 Page:161-174
ISSN:0824-7935
Container-title:Computational Intelligence
language:en
Short-container-title:Computational Intelligence

Author:

Maalouf Maher¹^ORCID,Homouz Dirar²,Trafalis Theodore B.³

Affiliation:

1. Industrial and Systems Engineering; Khalifa University; Abu Dhabi United Arab Emirates

2. Applied Mathematics and Science; Khalifa University; Abu Dhabi United Arab Emirates

3. Industrial and Systems Engineering; University of Oklahoma; Norman OK USA

Funder

Russell Sage Foundation

Publisher

Wiley

Subject

Artificial Intelligence,Computational Mathematics

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/coin.12123/fullpdf

Reference45 articles.

1. Rare events and imbalanced datasets: an overview;Maalouf;International Journal of Data Mining, Modelling, and Management,2011

2. Imbalanced Learning

3. Logistic regression in data analysis: an overview;Maalouf;International Journal of Data Analysis, Techniques and Strategies,2011

4. Karsmakers P Pelckmans K Suykens JAK Multi-class kernel logistic regression: a fixed-size implementation International Joint Conference on Neural Networks Orlando, FL 2007 1756 1761

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