Logistic regression in data analysis: an overview
M Maalouf - … Journal of Data Analysis Techniques and …, 2011 - inderscienceonline.com
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 …
in general and binary data classification in particular. This paper is focused on providing an …
Robust weighted kernel logistic regression in imbalanced and rare events data
M Maalouf, TB Trafalis - Computational Statistics & Data Analysis, 2011 - Elsevier
Recent developments in computing and technology, along with the availability of large
amounts of raw data, have contributed to the creation of many effective techniques and …
amounts of raw data, have contributed to the creation of many effective techniques and …
Weighted logistic regression for large-scale imbalanced and rare events data
M Maalouf, M Siddiqi - Knowledge-Based Systems, 2014 - Elsevier
Latest developments in computing and technology, along with the availability of large
amounts of raw data, have led to the development of many computational techniques and …
amounts of raw data, have led to the development of many computational techniques and …
[PDF][PDF] A modification of logistic regression with imbalanced data: F-measure-oriented Lasso-logistic regression
Logistic regression (LR) is one of the most popular classifiers. However, LR cannot perform
effectively on imbalanced data. There are two approaches to imbalanced data for LR …
effectively on imbalanced data. There are two approaches to imbalanced data for LR …