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The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial intelligence and machine learning, and presentation of the information extracted in a form that is without difficulty understandable to humans. Significant biological discoveries are now frequently made by combining data mining methods with the traditional laboratory techniques; an instance is the discovery of novel regulatory areas for heat shock genes in C. Elegans made by mining vast amounts of the gene expression and sequence data for the significant patterns.
This is acronym for the Epidemiological, Graphics, Estimation and Testing of the program developed for the analysis of the data from studies in epidemiology. It can be made in use
Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of
Human capital model : The model for evaluating the economic implication of the disease in terms of the economic loss of a person succumbing to morbidity or the mortality at some pa
Suppose the graph G is n-connected, regular of degree n, and has an even number of vertices. Prove that G has a one-factor. Petersen's 2-factor theorem (Theorem 5.40 in the note
Band matrix: A matrix which has its non zero elements arranged uniformly near to the diagonal, so that aij = 0 if (i - j)> ml or (j - i)> mu where aij are the elements of matrix a
Model is the description of the supposed structure of a set of observations which can range from a fairly imprecise verbal account to, more commonly, a formalized mathematical exp
stationary time series
McNemar's test is the test for comparing proportions in data involving the paired samples. The test statistic can be given by it is most useful when the data have a symmetri
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
Individual differences scaling is a form of multidimensional scaling applicable to the data comprising of a number of proximity matrices from the different sources that is differe
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