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clustering

Definition: Data clustering

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Clustering is a classic data mining technique based on machine learning that divides ​groups of abstract objects into classes of similar objects.

Clustering helps to split data into several subsets. Each of these clusters consists of data objects with high inter-similarity and low intra-similarity.

Clustering methods can be classified into the following categories:

  • Partitioning method
  • Hierarchical method
  • Density-based method
  • Grid-based method
  • Model-based method
  • Constraint-based method
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Clustering

Applications

Clustering helps to identify customers who have a certain customer record and similar conduct (i.e., buying patterns). In many applications (i.e., market research, pattern recognition, data and image processing), the clustering analysis is used in large numbers. Clustering can also help advertisers to find different groups within their customer base. For example, customer groups can be defined by buying patterns.

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machine learning
clustering
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Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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