Pattern Recognition

What Does Pattern Recognition Mean?

In IT, pattern recognition is a branch of machine learning that emphasizes the recognition of data patterns or data regularities in a given scenario. It is a subdivision of machine learning and it should not be confused with actual machine learning study. Pattern recognition can be either “supervised,” where previously known patterns can be found in a given data, or “unsupervised,” where entirely new patterns are discovered.

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Techopedia Explains Pattern Recognition

The objective behind pattern recognition algorithms is to provide a reasonable answer for all possible data and to classify input data into objects or classes based on certain features. A “most likely” matching is performed between various data samples and their key features are matched and recognized.

Pattern recognition and pattern matching are sometimes confused as the same thing when, in fact, they are not. Whereas pattern recognition looks for a similar or most likely pattern in a given data, pattern matching looks for exactly the same pattern. Pattern matching is not considered part of machine learning, although in some cases it leads to similar results as pattern recognition.

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Margaret Rouse

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical, business audience. Over the past twenty years her explanations have appeared on TechTarget websites and she's been cited as an authority in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine and Discovery Magazine.Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages. If you have a suggestion for a new definition or how to improve a technical explanation, please email Margaret or contact her…