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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.
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
Jelinski Moranda model is t he model of software reliability which supposes that failures occur according to the Poisson process with a rate decreasing as more faults are diagnos
Confidence interval : A range of the values, calculated from the sample observations which is believed, with the particular probability, to posses the true parameter value. A 95% c
Genstat: The basic purpose piece of statistical software for the management and the analysis of data. The package incorporates the wide variety of data handling events and a wi
Ha: If hyperlipidemia is believed to be a side effect of second-generation antipsychotics (SGAs), then Hispanic patients with SGAs treatment will have the higher frequency of devel
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
The act of combining data from heterogeneous sources with the intent of extracting information that would not be available for any single source in isolation. An example is the com
Multivariate analysis of variance is the procedure for testing equality of the mean vectors of more than two populations for the multivariate response variable. The method is dire
In the experimental studies, the collection of individuals to which the experimental process of interest is not applied. In the observational studies, most often used for a collect
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
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