What are the Common Clustering Algorithms Used in Business?
Several clustering algorithms are widely used in business applications:
1. K-Means Clustering: One of the most popular and straightforward algorithms, K-Means partitions data into k clusters based on centroids. It's widely used for market segmentation and customer profiling. 2. Hierarchical Clustering: This algorithm builds a hierarchy of clusters either through a bottom-up or top-down approach. It’s useful for organizing data into nested categories. 3. DBSCAN (Density-Based Spatial Clustering of Applications with Noise): DBSCAN identifies clusters based on the density of data points, making it effective for finding irregularly shaped clusters and dealing with noise. 4. Gaussian Mixture Models (GMM): GMM assumes that the data is generated from a mixture of several Gaussian distributions and is useful for clustering when the data distribution is complex.