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Sequential pattern mining is a topic of data mining concerned with finding statistically relevant patterns between data examples where the values are delivered in a sequence. [ 1 ] [ 2 ] It is usually presumed that the values are discrete, and thus time series mining is closely related, but usually considered a different activity.
Tree patterns are used in some programming languages as a general tool to process data based on its structure, e.g. C#, [1] F#, [2] Haskell, [3] Java [4], ML, Python, [5] Ruby, [6] Rust, [7] Scala, [8] Swift [9] and the symbolic mathematics language Mathematica have special syntax for expressing tree patterns and a language construct for ...
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent patterns.
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 ...
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
The second, or default case x -> 1 matches the pattern x against the argument and returns 1. This case is used only if the matching failed in the first case. The first, or special case matches against any compound, such as a non-empty list, or pair. Matching binds x to the left component and y to the right component. Then the body of the case ...
A Dictionary-based Compressed Pattern Matching Algorithm (PDF), archived from the original (PDF) on March 13, 2003 "A unifying framework for compressed pattern matching". 1999: 89– 96. CiteSeerX 10.1.1.50.1745. {{cite journal}}: Cite journal requires |journal= "Speeding Up String Pattern Matching by Text Compression: The Dawn of a New Era" (PDF).
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.