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Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizing some numerical index of the clustering. Since it is not possible to consider every partition of n individuals into g groups (because of the enormous number of the partitions), the algorithm starts with some given initial partition and considers individuals in turn for moving into the other clusters, creating the move if it causes an improvement in the value of the clustering index. The procedure is continued until no move of the single individual causes an improvement.
Probabilistic matching is a method developed to maximize the accuracy of the linkage decisions based on the level of agreement and disagreement among the identifiers on different
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows therefor
Described by the leading proponent as 'the conscientious, explicit, and judicious uses of present best evidence in making the decisions about the care of individual patients, and
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
The equation linking the height and weight of the children between the ages of 5 and 13 and given as follows here w is the mean weight in kilograms and h the mean height in
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
Confidence profile method : A Bayesian approach to meta-analysis in which the information in each piece of the evidence is captured in the likelihood function which is then used al
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
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