Pattern recognition systems are deleted from labeled "training" data.
Pattern recognition is a branch of machine learning that focuses on the recognition of patterns and regularities in data , although it is in some cases considered to be nearly synonymous with machine learning .. machine learning. machine learning. data. data. Pattern recognition systems are in many cases trained from labeled `` training '' data -LRB- supervised learning -RRB- , but when no labeled data are available other algorithms can be used to discover previously unknown patterns -LRB- unsupervised learning -RRB- .. data. data. supervised learning. supervised learning. unsupervised learning. unsupervised learning. The terms pattern recognition , machine learning , data mining and knowledge discovery in databases -LRB- KDD -RRB- are hard to separate , as they largely overlap in their scope .. machine learning. machine learning. data. data. data mining. data mining. knowledge discovery in databases. knowledge discovery in databases. Machine learning is the common term for supervised learning methods and originates from artificial intelligence , whereas KDD and data mining have a larger focus on unsupervised methods and stronger connection to business use .. data. data. supervised learning. supervised learning. data mining. data mining. artificial intelligence. artificial intelligence. Pattern recognition has its origins in engineering , and the term is popular in the context of computer vision  : a leading computer vision conference is named Conference on Computer Vision and Pattern Recognition .. engineering. engineering. computer vision. computer vision. Conference on Computer Vision and Pattern Recognition. Conference on Computer Vision and Pattern Recognition. In pattern recognition , there may be a higher interest to formalize , explain and visualize the pattern , while machine learning traditionally focuses on maximizing the recognition rates .. machine learning. machine learning. Yet , all of these domains have evolved substantially from their roots in artificial intelligence , engineering and statistics , and they 've become increasingly similar by integrating developments and ideas from each other .. artificial intelligence. artificial intelligence. engineering. engineering. In machine learning , pattern recognition is the assignment of a label to a given input value .. machine learning. machine learning. In statistics , discriminant analysis was introduced for this same purpose in 1936 .. discriminant analysis. Linear discriminant analysis. An example of pattern recognition is classification , which attempts to assign each input value to one of a given set of classes -LRB- for example , determine whether a given email is `` spam '' or `` non-spam '' -RRB- .. classification. classification ( machine learning ). However , pattern recognition is a more general problem that encompasses other types of output as well .. 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 -LRB- for example , part of speech tagging , which assigns a part of speech to each word in an input sentence -RRB- ; and parsing , which assigns a parse tree to an input sentence , describing the syntactic structure of the sentence .. regression. regression analysis. sequence labeling. sequence labeling. part of speech tagging. part of speech tagging. part of speech. part of speech. parsing. parsing. parse tree. parse tree. syntactic structure. syntactic structure. Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to perform `` most likely '' matching of the inputs , taking into account their statistical variation .. This is opposed to pattern matching algorithms , which look for exact matches in the input with pre-existing patterns .. pattern matching. pattern matching. A common example of a pattern-matching algorithm is regular expression matching , which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors .. data. data. regular expression. regular expression. In contrast to pattern recognition , pattern matching is generally not considered a type of machine learning , although pattern-matching algorithms -LRB- especially with fairly general , carefully tailored patterns -RRB- can sometimes succeed in providing similar-quality output of the sort provided by pattern-recognition algorithms .. machine learning. machine learning. pattern matching. pattern matching