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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.
Jonckheere Terpstra test is the test for detecting particular types of departures from the independence in a contingency table in which both the row and column categories contain
Multitrait multi method model (MTMM) is the form of confirmatory factor analysis model in which the different techniques of measurement are used to measure each of the latent vari
The distribution free or technique which is the analogue of the analysis of variance for the design with two factors. It can be applied to data sets which do not meet the assumptio
Kurtosis: The extent to which the peak of the unimodal probability distribution or the frequency distribution departs from its shape of the normal distribution, by either being mo
Quittingill effect is a problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms
Imprecise probabilities is a n approach used by soft techniques in which uncertainty is represented by the closed, convex sets of probability distributions and the probability of
need answers to questions in book advanced and multivariate statistical methods
VIF is the abbreviation of variance inflation factor which is a measure of the amount of multicollinearity that exists in a set of multiple regression variables. *The VIF value
how to describe association between quantitative and categorical variables
The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
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