Logistic regression in data analysis: An overview

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    171 Scopus citations

    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.

    Original languageBritish English
    Pages (from-to)281-299
    Number of pages19
    JournalInternational Journal of Data Analysis Techniques and Strategies
    Volume3
    Issue number3
    DOIs
    StatePublished - 2011

    Keywords

    • Classification
    • Data mining
    • Imbalanced data
    • Logistic regression
    • LR
    • Rare events

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