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.

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

Medical datasets often present a major challenge for machine learning models: skewness in continuous variables such as age, ...

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams ...

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 ...

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

There are many different optimization algorithms that can be used to find good values for logistic regression weights and bias. Four of the most commonly used techniques are iterated Newton-Raphson, L ...

Logistic regression is a statistical tool that forms much of the basis of the field of machine learning and artificial intelligence, including prediction algorithms and neural networks.

As defined on TechTarget, logistic regression is a statistical analysis method used to predict a data value based on prior observations of a data set. A logistic regression model predicts a ...