Comparison of Logistic Regression and Linear Discriminant Analysis : A Simulation Study

@inproceedings{Pohar2004ComparisonOL,
  title={Comparison of Logistic Regression and Linear Discriminant Analysis : A Simulation Study},
  author={Maja Perme Pohar and Mateja Blas and Sandra Turk},
  year={2004}
}
Two of the most widely used statistical methods for analyzing categorical outcome variables are linear discrimina nt nalysis and logistic regression. While both are appropriate for the deve lopment of linear classification models, linear discriminant analysis makes more assumptions about the underlying data. Hence, it is assumed tha t logistic regression is the more flexible and more robust method in case of vi lations of these assumptions. In this paper we consider the problem of choosing… CONTINUE READING

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