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The term used for the estimation of the misclassification rate in the discriminant analysis. Number of techniques has been proposed for two-group situation, but the multiple-group situation has rarely been addressed. The easiest procedure is the resubstitution technique, in which the training data are classified using the estimated classification rule and proportion incorrectly placed used as the estimate of misclassification rate. This technique is known to have a large optimistic bias, but it has the benefit that it can be applied to the multigroup problems with no modification required. An alternative technique is the leave one out estimator, in which each of the observation in turn is removed from the data and the classification rule recomputed using remaining data. The proportion improperly classified by the procedure will have reduced bias compared to resubstitution technique. This method can also be implied to the multi group problem with no modification but it has the large amount of variance.
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
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a sequence of numbers consist of six 6''s seven 7''s eight 8''s nine 9''s ten 10''s what is the arithmetic mean?
This process of estimating from a data set those values lying beyond range of the data. In the regression analysis, for instance, a value of the response variable might be estimate
how does it work exactly
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The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
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