Clustering Algorithm

A clustering algorithm is a type of unsupervised machine learning algorithm that groups similar data points together based on their characteristics or features. The goal of clustering is to identify patterns or structures in the data that may not be immediately apparent. Clustering algorithms can be used for a variety of tasks, such as customer segmentation, anomaly detection, and image recognition. There are several types of clustering algorithms, including hierarchical clustering, k-means clustering, and density-based clustering. Hierarchical clustering creates a tree-like structure of clusters, while k-means clustering partitions the data into a predetermined number of clusters. Density-based clustering identifies areas of high density in the data and groups points together based on their proximity to these areas.
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