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Example of cup and handle chart pattern. In the domain of technical analysis of market prices, a cup and handle or cup with handle formation is a chart pattern consisting of a drop in the price and a rise back up to the original value, followed first by a smaller drop and then a rise past the previous peak. [1]
A modern definition of pattern recognition is: The field of pattern recognition is concerned with the automatic discovery of regularities in data through the use of computer algorithms and with the use of these regularities to take actions such as classifying the data into different categories.
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
Bjarne Stroustrup (/ ˈ b j ɑːr n ə ˈ s t r ɒ v s t r ʊ p /; Danish: [ˈbjɑːnə ˈstʁʌwˀstʁɔp]; [3] [4] born 30 December 1950) is a Danish computer scientist, known for the development of the C++ programming language. [5]
Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.
In computer science, the Krauss wildcard-matching algorithm is a pattern matching algorithm. Based on the wildcard syntax in common use, e.g. in the Microsoft Windows command-line interface, the algorithm provides a non-recursive mechanism for matching patterns in software applications, based on syntax simpler than that typically offered by regular expressions.
The Rete algorithm (/ ˈ r iː t iː / REE-tee, / ˈ r eɪ t iː / RAY-tee, rarely / ˈ r iː t / REET, / r ɛ ˈ t eɪ / reh-TAY) is a pattern matching algorithm for implementing rule-based systems. The algorithm was developed to efficiently apply many rules or patterns to many objects, or facts, in a knowledge base. It is used to determine ...