Clustering is a technique used in machine learning and data analysis to group a set of objects in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups.
Characteristics:
– Unsupervised learning method, meaning it does not rely on labeled data.
– Groups data points based on similarity or distance metrics.
– Helps identify natural groupings or patterns within data.
– Can handle large datasets and various types of data.
– Common algorithms include K-means, hierarchical clustering, and DBSCAN.
Examples:
– Customer segmentation in marketing to target specific groups.
– Organizing news articles into topics.
– Image segmentation in computer vision.
– Grouping similar documents or emails for easier retrieval.
