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 is the main method to deal with data classification in the field of large data and machine learning. The traditional logistic regression uses gradient descent method to solve the ...

Sparse logistic regression is for classification and feature selection simultaneously. Although many studies have been done to solve $\\ell_{1}$-regularized logistic regression, there is no ...

Machine learning basic training with examples. Contribute to MykolasR/Machine-learning-training development by creating an account on GitHub.

ML_BASICS_Logistic_Regression_with_Python This is a neat way of taking the linear equation we used in the Linear Regression tutorial and manipulating it to deal with non-linear problems such as Binary ...

Types of Logistic Regression: Binary Logistic Regression Only two possible outcomes (Category). Example: The person will buy a car or not. Multinomial Logistic Regression More than two Categories ...

Many machine learning code libraries have built-in multi-class logistic regression functionality. However, coding multi-class logistic regression from scratch has least four advantages over using a ...