Machine Learning for OpenCV 4 - Second Edition

Selecting the Right Model with Hyperparameter Tuning

Now that we have explored a wide variety of machine learning algorithms, I am sure you have realized that most of them come with a great number of settings to choose from. These settings or tuning knobs, the so-called hyperparameters, help us to control the behavior of the algorithm when we try to maximize performance.

For example, we might want to choose the depth or split criterion in a decision tree or tune the number of neurons in a neural network. Finding the values of important parameters of a model is a tricky task but necessary for almost all models and datasets.

In this chapter, we will dive deeper into model evaluation and hyperparameter tuning. Assume that we have two different ...