Clustering Models
Clustering models are unsupervised machine learning algorithms that group similar data points into clusters based on their features, without using predefined labels. They identify patterns and structures in data by partitioning it into subsets where points within a cluster are more similar to each other than to those in other clusters. Common applications include customer segmentation, anomaly detection, and image compression.
Developers should learn clustering models when working with unlabeled data to discover hidden patterns, reduce dimensionality, or preprocess data for further analysis. They are essential in fields like marketing for customer segmentation, biology for gene expression analysis, and cybersecurity for detecting outliers or anomalies in network traffic.