Cluster Analysis

Cluster Analysis is a technique used in Data Science and Artificial Intelligence to group similar data points together based on their characteristics. It is an unsupervised learning method that involves identifying patterns in data without prior knowledge of the outcome. The goal of cluster analysis is to divide a dataset into meaningful and distinct groups, or clusters, that can be used for further analysis or decision-making. There are several methods of cluster analysis, including hierarchical clustering, k-means clustering, and density-based clustering. Each method has its own strengths and weaknesses, and the choice of method depends on the nature of the data and the research question. Cluster analysis is widely used in various fields, such as marketing, biology, and social sciences, to identify customer segments, gene expression patterns, and social networks, respectively.
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