15.1 Clustering
15.1.1 What is Clustering?
Clustering is a powerful technique in machine learning that involves the process of dividing a dataset into groups or clusters based on similarities among data points. The main objective of clustering is to partition the data in a way that data points in the same group are more similar to each other than to those in other groups. This technique can be used in a variety of fields, including marketing, social media analysis, and customer segmentation. For instance, a marketing team can use clustering to develop a better understanding of their customer base by grouping them into different segments based on their purchasing behavior, preferences, and demographics.
The clustering process involves several steps, including selecting an appropriate clustering algorithm, determining the number of clusters, and identifying the features or variables to be used. There are several types of clustering algorithms, including k-means, hierarchical clustering...