en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

In pattern recognition, the k-Nearest Neighbors algorithm is a non-parametric
method used for classification and regression. In both cases, the input consists of
...

scikit-learn.org/stable/modules/neighbors.html

NearestNeighbors implements unsupervised nearest neighbors learning. It acts
as a uniform interface to three different nearest neighbors algorithms: BallTree ...

www.ask.com/youtube?q=Nearest Neighbors&v=UqYde-LULfs

Feb 18, 2014 ... In this video I describe how the k Nearest Neighbors algorithm works, and
provide a simple example using 2-dimensional data and k = 3.

www.statsoft.com/Textbook/k-Nearest-Neighbors

To demonstrate a k-nearest neighbor analysis, let's consider the task of
classifying a new object (query point) among a number of known examples. This
is ...

www.saedsayad.com/k_nearest_neighbors.htm

K nearest neighbors is a simple algorithm that stores all available cases and
classifies new cases based on a similarity measure (e.g., distance functions).

machinelearningmastery.com/k-nearest-neighbors-for-machine-learning/

Apr 15, 2016 ... In this post you will discover the k-Nearest Neighbors (KNN) algorithm for
classification and regression. After reading this post you will know.

saravananthirumuruganathan.wordpress.com/2010/05/17/a-detailed-introduction-to-k-nearest-neighbor-knn-algorithm/

May 17, 2010 ... K Nearest Neighbor (KNN from now on) is one of those algorithms that are very
simple to understand but works incredibly well in practice.

www.analyticsvidhya.com/blog/2014/10/introduction-k-neighbours-algorithm-clustering/

Oct 10, 2014 ... In this article, we will talk about another widely used classification technique
called K-nearest neighbors (KNN) . Our focus will be primarily on ...

dmg.org/v4-1/KNN.html

k-Nearest Neighbors (k-NN) is an instance-based learning algorithm. In a k-NN
model, a hypothesis or generalization is built from the training data directly at the
...