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Clustering Meaning: Definition, Examples, and Translations

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clustering

[หˆklสŒstษ™rษชล‹ ]

Definitions

Context #1 | Noun

data analysis

Clustering is a method used in statistical data analysis where elements are grouped based on their similarities. It helps to identify patterns and structures within datasets by organizing data into meaningful clusters. This technique has widespread applications in machine learning, with various algorithms like K-means and hierarchical clustering utilized for efficient data segmentation. Clustering is essential in exploring and interpreting large volumes of information, making it easier to draw insightful conclusions.

Synonyms

classification, grouping, segmentation.

Examples of usage

  • The clustering of customer data revealed distinct purchasing behaviors.
  • We used clustering techniques to segment the market into different demographics.
  • Clustering algorithms helped us identify groups of similar diseases in our research.
Context #2 | Noun

biology

In biology, clustering refers to the natural grouping of organisms that share common characteristics or behaviors. This can include the clustering of species based on evolutionary traits or ecological niches. Understanding these clusters can help in studying biodiversity and ecological interactions, as well as in conducting conservation efforts to protect endangered species.

Synonyms

aggregation, bunching, congregation.

Examples of usage

  • The clustering of similar species in the rainforest allows for better ecological study.
  • Researchers observed clustering patterns among migratory birds.
  • Clustering in genetics can reveal how species have evolved over time.

Translations

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Origin of 'clustering'

The term 'clustering' derives from the word 'cluster', which has roots in Middle English 'clustre' and Old French 'clostre', meaning 'to cluster together'. The concept became particularly significant in the realm of mathematics and statistics in the 20th century, where its application expanded rapidly with the rise of data analysis and computational techniques. With the advent of computer science and machine learning, clustering has emerged as a vital method in data mining, enabling the organization of vast amounts of information into comprehensible groups. As the digital age continues to evolve, clustering techniques are increasingly being applied in numerous fields, including marketing, biology, and social research, making it a fundamental concept in understanding complex systems.

Word Frequency Rank

Ranked #11,316, this word falls into high-advanced vocabulary. It appears less frequently but is valuable for expressing precise meanings in specific contexts.