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Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application including optical character recognition. Speech recognition, remote sensing and medical imaging processing. Because 'recognition' is almost synonymous with 'classification' in this field, pattern recognition includes statistical classification techniques such as discriminant analysis (here known as supervised pattern recognition or supervised learning) and cluster analysis (known as unsupervised pattern recognition or unsupervised learning). Pattern recognition is closely related to artificial intelligence, artificial neural networks and machine learning and is one of the main techniques used in data mining. Perhaps the distinguishing feature of pattern recognition is that no direct analogy is made in its methodology to underlying biological processes.
methods of measuring trend
The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
An oil company is considering whether or not to bid for an offshore drilling contract. If they bid, the value would be $600m with a 65% chance of gaining the contract. The company
Group visible design is an arrangement of the v mn treatments in b blocks such that: * Each block comprises k distinct treatments k5v; * Each treatment is replicated r number
Non linear mapping (NLM ) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences
How do I report the results in the table?
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Generally the final stage of an exploratory factor analysis in which factors derived initially are transformed to build their interpretation simpler. Generally the target of the pr
importance of mathamatical expection in business
This is an approach to the modelling of time-frequency surfaces which consists of a Bayesian regularization scheme in which the prior distributions over the time-frequency coeffici
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