In these scenarios, a common approach involves developing both a linear regression model and a logistic classification model with the same dataset and deploying them sequentially.

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 ...

Dimitris Bertsimas, Angela King, Logistic Regression: From Art to Science, Statistical Science, Vol. 32, No. 3 (August 2017), pp. 367-384 ...

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.

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 ...