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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.
Regression to the mean is the procedure first noted by Sir Francis Galton that 'each peculiarity in man is shared by his kinsmen, but on average to the less degree.' Hence the ten
what is measures of variability?
Law of likelihood : Within framework of the statistical model, a particular set of data supports one statistical hypothesis or assumption better than another if the likelihood of t
Intercropping experiments are the experiments including growing two or more crops at same time on the same patch of land. The crops are not required to be planted nor harvested at
The probability distribution of the various observations is required to obtain the run of two successes in the series of Bernoulli trials with the probability of success equal to a
High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st
Yate s' continuity correction : When the testing for independence in contingency table, a continuous probability distribution, known as chi-squared distribution, is used as the app
Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu
Johnson-Neyman technique: The technique which can be used in the situations where analysis of the covariance is not valid because of the heterogeneity of slopes. With this method
Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is
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