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Revision as of 12:01, 10 February 2025

Classification is the process of arranging entities into groups based on shared characteristics or criteria. It is a fundamental concept in various fields such as biology, library science, information science, and machine learning. Classification helps in organizing information, making it easier to retrieve, analyze, and understand.

Types of Classification

Classification can be broadly categorized into several types:

Hierarchical Classification

Hierarchical classification involves organizing entities into a tree-like structure where each level represents a different degree of specificity. This type is commonly used in taxonomy to classify living organisms.

Flat Classification

Flat classification, also known as single-level classification, involves grouping entities into non-overlapping categories without any hierarchical structure. This is often used in document classification and spam filtering.

Supervised Classification

In supervised classification, a model is trained on a labeled dataset, where the correct output is known. This type is prevalent in machine learning applications such as image recognition and natural language processing.

Unsupervised Classification

Unsupervised classification, or clustering, involves grouping entities based on inherent similarities without prior labeling. This is used in data mining and pattern recognition.

Applications of Classification

Classification has numerous applications across different domains:

Biology

In biology, classification is used to organize living organisms into groups such as kingdom, phylum, class, order, family, genus, and species. This hierarchical system is known as biological classification or taxonomy.

Library Science

In library science, classification systems like the Dewey Decimal Classification and the Library of Congress Classification are used to organize books and other materials in libraries.

Information Science

In information science, classification helps in organizing and retrieving information efficiently. Techniques such as metadata tagging and ontology development are used for this purpose.

Machine Learning

In machine learning, classification algorithms such as decision trees, support vector machines, and neural networks are used to categorize data into predefined classes.

Related Pages

See Also




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