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An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is "spam"). Pattern recognition is a more general problem that encompasses other types of output as well.
In psychology and cognitive neuroscience, pattern recognition is a cognitive process that matches information from a stimulus with information retrieved from memory. [1]Pattern recognition occurs when information from the environment is received and entered into short-term memory, causing automatic activation of a specific content of long-term memory.
In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects, since such representations facilitate processing and statistical analysis.
With the increasing automation of services, more and more decisions are being made by algorithms. Some general examples are; risk assessments, anticipatory policing, and pattern recognition technology. [1] The following is a list of well-known algorithms along with one-line descriptions for each.
Other examples are regression, which assigns a real-valued output to each input; sequence labeling, which assigns a class to each member of a sequence of values (for example, part of speech tagging, which assigns a part of speech to each word in an input sentence); parsing, which assigns a parse tree to an input sentence, describing the ...
This helps divide the recognition task into easier subtasks of first identifying sub-patterns, and then the actual patterns. Structural methods provide descriptions of items, which may be useful in their own right. For example, syntactic pattern recognition can be used to determine what objects are present in an image. Furthermore, structural ...
An example Bongard problem, the common factor of the left set being convex shapes (the right set are instead all concave). A Bongard problem is a kind of puzzle invented by the Soviet computer scientist Mikhail Moiseevich Bongard (Михаил Моисеевич Бонгард, 1924–1971), probably in the mid-1960s.
"Pattern mining" is a data mining method that involves finding existing patterns in data. In this context patterns often means association rules . The original motivation for searching association rules came from the desire to analyze supermarket transaction data, that is, to examine customer behavior in terms of the purchased products.