This article will explain the concept of data classification based on K-Nearest Neighbor Algorithm of Machine Learning
IntroductionK-Nearest Neighbour (KNN) is a basic classification algorithm of Machine Learning. It comes under supervised learning. It is often used in the solution of classification problems in the industry. It is widely used in pattern recognization, data mining, etc. It stores all the available cases from training dataset and classifies the new cases based on distance function. I will explain KNN algorithm with the help of "Euclidean Distance" formula.Euclidean Distance Euclidean distance formula is used to measure the distance in the plane. It is a very famous way to get the distance between two points.Let's say the points (x1, y1) and (x2, y2) are points in 2-dimensional space and distance by using the Pythagorean formula like below.
This training data includes classification with given x, y values.
This set of training data doesn't contain classification type. So, it will be predicted.
Pro WPF: Windows Presentation Foundation in .NET 3.0