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.