Hello everyone, hope you had a wonderful Christmas! In this post I will show you how to do k means clustering in R. We will use the iris dataset from the datasets library. What is K Means Clustering? K Means Clustering is an unsupervised learning algorithm that tries to cluster data based on their similarity.

Chapter 15 CLUSTERING METHODS Lior Rokach Department of Industrial Engineering Tel-Aviv University liorr@eng.tau.ac.il Oded Maimon Department of Industrial Engineering Tel-Aviv University maimon@eng.tau.ac.il Abstract This chapter presents a tutorial overview of the main clustering methods used in Data Mining. Cluster Analysis: Tutorial with R Jari Oksanen January 26, 2014 Contents 5 Fuzzy Clustering 12 1 Introduction In this tutorial we inspect classi cation. Classi cation and ordination are al- fusion level in the cluster dendrogram would be the length of the corresponding Hierarchical clustering: Hierarchical methods use a distance matrix as an input for the clustering algorithm. The choice of an appropriate metric will influence the shape of the clusters, as some elements may be close to one another according to one distance and farther away according to another. With the distance matrix found in previous tutorial, we can use various techniques of cluster analysis for relationship discovery. For example, in the data set mtcars, we can run the distance matrix with hclust, and plot a dendrogram that displays a hierarchical relationship among the vehicles. Clustering Tutorial What is Clustering? Clustering is the use of multiple computers, typically PCs or UNIX workstations, multiple storage devices, and redundant interconnections, to form what appears to users as a single highly available system. Cluster computing can be used for load balancing as well as for high availability. It is used Introduction to K-means Clustering: A Tutorial. Dr. Andrea Trevino presents a beginner introduction to the widely-used K-means clustering algorithm in this tuto