Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Logistic regression is a technique used to make predictions in situations where the item to predict can take one of just two possible values. For example, you might want to predict the credit ...

First off, you need to be clear what exactly you mean by advantages. People have argued the relative benefits of trees vs. logistic regression in the context of interpretability, robustness, etc.

Kin-Yee Chan, Wei-Yin Loh, LOTUS: An Algorithm for Building Accurate and Comprehensible Logistic Regression Trees, Journal of Computational and Graphical Statistics, Vol. 13, No. 4 (Dec., 2004), pp.

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Logistic regression is preferrable over a simpler statistical test such as chi-squared test or Fisher’s exact test as it can incorporate more than one explanatory variable and deals with possible ...

The is sometimes called multi-class logistic regression. But in my opinion, using an alternative classification technique, a neural network classifier, is a better option. Logistic regression can ...