Description
Understand logistic regression with a real-world case study, visualize the mathematics and geometric interpretation for classification tasks
Summary
- Purpose This article will help you understand logistic regression at an intuitive level with the help of a case study inspired by a real-world example.
- Logistic Regression for classification is an ideal algorithm to have as a benchmark.
- Image by Author) Once you have the cost function defined, all you need to do now is run an optimization algorithm and find the value of the unknowns that can help get you the minimum.
- Image by Author) The Prediction Finally, if we need to make prediction on a new dataset, all we need to do is get their HR and BR, and use the parameter values found (A,B, and C) during learning to find out the predicted output, y. Graphically, this would be equivalent to determining which side of the decision boundary the new data point lies in.