 k-nearest neighbors algorithm

The K-nearest neighbors (KNN) algorithm is a simple and widely-used machine learning algorithm primarily used for classification and regression tasks. It is a type of instance-based learning, meaning it makes predictions based on the instances (data points) that are stored in the training set. ### Key Concepts: 1. **Instance-based learning**: KNN stores all of the training instances and makes decisions based on the instances it finds most similar to new data.

One of the most simply classification algorithm one can think of: just see whatever kind of point your new point seems to be closer to, and say it is also of that type! Then it is just a question of defining "close".

Scikit-learn implementation scikit-learn.org/stable/auto_examples/neighbors/plot_classification.html at python/sklearn/knn.py