Introduction to the Random Search Method

What is the random search method?

The random search method is a simple approach for hyperparameter optimization in ML. It is a popular technique widely used by practitioners because of its simplicity and ease of implementation. We’ll learn its theory and how to apply it in a simple ML project using the open-source Python library called scikit-learn.

The random search method involves selecting random combinations of hyperparameter values of a particular ML algorithm, such as logistic regression. Then it evaluates the performances of the ML model using the selected combination of hyperparameter values.

It repeats this process for a fixed number of iterations with different combinations of hyperparameter values that are randomly selected. This can be done by defining a range of values for each hyperparameter and then randomly sampling from these ranges for each iteration.