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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.
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
what is operational gaining
Projection pursuit is a procedure for attaning a low-dimensional (usually two-dimensional) representation of the multivariate data, which will be particularly useful in revealing
The number of employees absent from work at a large electronics manufacturing plant over aperiod of 106 days is given in the table below. 146 141 139 140 145 141 142 131 142 140
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
Captures recapture sampling : Another approach to a census for estimating the size of population, which operates by sampling the population number of times, identifying the individ
Quincunx is the device used by Galton to illustrate his lectures, which is shown in the Figure. It had a glass face and a funnel at its top. The shot was passed through funnel an
Data which occur when failure period is recorded which are dependent. Such type of data can arise in number contexts, for instance, in epidemiological cohort studies in which th
stationary time series
1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch
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