Radius Neighbors Classifier Algorithm With Python
Radius Neighbors Classifier is a classification machine learning algorithm.
It is an extension to the k-nearest neighbors algorithm that makes predictions using all examples in the radius of a new example rather than the k-closest neighbors.
As such, the radius-based approach to selecting neighbors is more appropriate for sparse data, preventing examples that are far away in the feature space from contributing to a prediction.
In this tutorial, you will discover the Radius Neighbors Classifier classification machine learning algorithm.
After completing this tutorial, you will know:
- The Nearest Radius Neighbors Classifier is a simple extension of the k-nearest neighbors classification algorithm.
- How to fit, evaluate, and make predictions with the Radius Neighbors Classifier model with Scikit-Learn.
- How to tune the hyperparameters of the Radius Neighbors Classifier algorithm on a given dataset.
Let’s get started.
Radius Neighbors Classifier Algorithm With Python
Photo by J. Triepke, some rights reserved.
Tutorial Overview
This tutorial is divided into three parts; they are:
- Radius Neighbors Classifier
- Radius Neighbors Classifier With Scikit-Learn
- Tune Radius Neighbors