Pattern recognition
Pattern Recognition
Pattern recognition (/ˈpætərn rɛkəɡˈnɪʃən/) is a branch of Artificial Intelligence that focuses on the recognition of patterns and regularities in data.
Etymology
The term "pattern recognition" is derived from the ability to identify patterns, a fundamental aspect of human cognition. The term was first used in the context of Artificial Intelligence in the mid-20th century.
Definition
Pattern recognition involves classifying data into predefined categories. A pattern can be defined in various ways, including a template or feature set. In Machine Learning, pattern recognition is an important part of the learning process, where an algorithm learns to recognize patterns in the input data and make predictions based on these patterns.
Related Terms
- Artificial Intelligence: The science of making machines or software that can perform tasks that would normally require human intelligence.
- Machine Learning: A type of artificial intelligence that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.
- Data Mining: The process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
- Neural Networks: A series of algorithms that attempts to identify underlying relationships in a set of data through a process that mimics the way the human brain operates.
Applications
Pattern recognition has a wide range of applications in the medical field. It is used in Medical Imaging for the detection of diseases, in Genomics for the identification of genetic patterns, and in Epidemiology for the prediction of disease outbreaks.
See Also
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