Decision Boundary in Machine Learning

The general goal of a classification model is to find a decision boundary. The purpose of the decision boundaries is to identify those regions of the input class space that corresponds to each class. In this article, I will take you through the concept of decision boundary in machine learning. To explain the concept of decision boundaries in machine learning, I will first create a Logistic Regression model. So now let's import some libraries and get started with the task: I will use the iris dataset to fit a Linear Regression model.