Grammatical Inference
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Grammatical Inference
Grammar induction (or grammatical inference) is the process in machine learning of learning a formal grammar (usually as a collection of ''re-write rules'' or '' productions'' or alternatively as a finite-state machine or automaton of some kind) from a set of observations, thus constructing a model which accounts for the characteristics of the observed objects. More generally, grammatical inference is that branch of machine learning where the instance space consists of discrete combinatorial objects such as strings, trees and graphs. Grammar classes Grammatical inference has often been very focused on the problem of learning finite-state machines of various types (see the article Induction of regular languages for details on these approaches), since there have been efficient algorithms for this problem since the 1980s. Since the beginning of the century, these approaches have been extended to the problem of inference of context-free grammars and richer formalisms, such as mult ...
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Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ...
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John Koza
John R. Koza is a computer scientist and a former adjunct professor at Stanford University, most notable for his work in pioneering the use of genetic programming for the optimization of complex problems. Koza co-founded Scientific Games Corporation, a company which builds computer systems to run state lotteries in the United States. John Koza is also credited with being the creator of the ' scratch card' with the help of retail promotions specialist Daniel Bower. Koza was born in 1944 and earned a bachelor's degree in computer science from the University of Michigan, being the second person to ever earn a bachelor's degree in computer science. He earned a doctoral degree in computer science from the University of Michigan in 1972. Koza was featured in Popular Science for his work on evolutionary programming that alters its own code to find far more complex solutions. The machine, which he calls the "invention machine", has created antennae, circuits, and lenses, and has recei ...
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Pumping Lemma For Regular Languages
In the theory of formal languages, the pumping lemma for regular languages is a Lemma (mathematics), lemma that describes an essential property of all regular languages. Informally, it says that all sufficiently long string (computer science), strings in a regular language may be ''pumped''—that is, have a middle section of the string repeated an arbitrary number of times—to produce a new string that is also part of the language. The pumping lemma is useful for proving that a specific language is not a regular language, by showing that the language does not have the property. Specifically, the pumping lemma says that for any regular language L, there exists a constant p such that any string w in L with length at least p can be split into three substrings x, y and z (w = xyz, with y being non-empty), such that the strings xz, xyz, xyyz, xyyyz, ... are also in L. The process of repeating y zero or more times is known as "pumping". Moreover, the pumping lemma guarantees that the ...
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