Logistic Regression

Logistic Regression is a method used to predict the probability of a categorical outcome. Instead of predicting a continuous value, it predicts whether something belongs to a certain category (like yes/no, true/false, or 0/1). It does this by using a logistic function (also known as a sigmoid function) to squeeze the output of a linear equation between 0 and 1, representing the probability of belonging to that category. The model learns the best coefficients for the linear equation based on the training data.

Visit the following resources to learn more:

• @article@Logistic Regression | scikit-learn
• @article@Understanding Logistic Regression in Python
• @video@Hands-On Machine Learning: Logistic Regression with Python and Scikit-Learn