Clustering
Clustering is a technique in data analysis in which data are grouped based on their similarity to each other. The purpose of clustering is to divide a set of data into different groups (clusters) so that the data within each group are more similar to each other than to the data in other groups.
An example of clustering is grouping customers of a supermarket based on their purchasing behavior. A clustering algorithm could be used to group customers who often buy the same products or store in the same aisles. This can provide valuable information to the marketing department, which can use this information to create targeted ads and offers for each group of customers.
A clustering algorithm
A commonly used clustering algorithm is k-means clustering, in which the number of clusters is predetermined. The goal is to group each data point in the dataset into one of k clusters based on their spacing. The algorithm calculates the average of all data points in each cluster and adjusts this average until there is no change. This results in a set of clusters, each consisting of data points that are more similar to each other than to the data points in other clusters.