Time frame: 1 May 2024 - 30 April 2025 Institution search supports local language names. , Home Articles Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Ji Zhu, Trevor Hastie, Kernel Logistic Regression and the Import Vector Machine, Journal of Computational and Graphical Statistics, Vol. 14, No. 1 (Mar., 2005), pp. 185-205 ...

Logistic regression is a machine learning technique for binary classification. For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, ...

This article will cover the basic theory behind logistic regression, the types of logistic regression, when to use them and take you through a worked example.

Logistic regression analysis of high-dimensional data, such as natural language text, poses computational and statistical challenges. Maximum likelihood estimation often fails in these applications.

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 ...