David Tritchler, An Algorithm for Exact Logistic Regression, Journal of the American Statistical Association, Vol. 79, No. 387 (Sep., 1984), pp. 709-711 ...

Regression can be used on categorical responses to estimate probabilities and to classify.

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.

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data scientists should master both supervised ...

Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

Logistic regression is considered a type of supervised machine learning algorithm. Advantages of the method in this setting include that it is interpretable, simple to understand and can be ...

The LOGISTIC and PROBIT procedures can perform logistic and ordinal logistic regression. See Chapter 5, "Introduction to Categorical Data Analysis Procedures," Chapter 39, "The LOGISTIC Procedure," ...

This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...