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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.
Interior analysis is the term now and again applied to analysis carried out on the fitted model in regression problem. The basic target of such analyses is the identification of
Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of
Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular
Multimodal distribution is the probability distribution or frequency distribution with number of modes. Multimodality is frequently taken as an indication which the observed di
This is an attempt to measure the suffering caused by the illness which takes into the account both the years of the potential life lost due to the premature mortality as well as t
O'Brien's two-sample tests are the extensions of the conventional tests for assessing the differences between treatment groups which take account of the possible heterogeneous nat
In an experiment, power is a function of 1. The number of variables being measured and the beta level 2. The effect size, internal validity and the beta level 3. The number of part
Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo
Range is the difference between the largest and smallest observations in the data set. Commonly used as an easy-to-calculate measure of the dispersion in the set of observations b
Hazard regression is the procedure for modeling the hazard function which does not depend on the suppositions made in Cox's proportional hazards model, namely that the log-hazard
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