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Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application including optical character recognition. Speech recognition, remote sensing and medical imaging processing. Because 'recognition' is almost synonymous with 'classification' in this field, pattern recognition includes statistical classification techniques such as discriminant analysis (here known as supervised pattern recognition or supervised learning) and cluster analysis (known as unsupervised pattern recognition or unsupervised learning). Pattern recognition is closely related to artificial intelligence, artificial neural networks and machine learning and is one of the main techniques used in data mining. Perhaps the distinguishing feature of pattern recognition is that no direct analogy is made in its methodology to underlying biological processes.
Window variables are the variables measured during the constrained interval of an observation period which is accepted as the proxies for the information over the whole period. Fo
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is oil in the ground, the soil test comes
The regression analysis is used to fit a model describing the relationship of a dependent variable with independent variable(s). Here we have fitted three regression models:
Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor v
The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the
Post stratification adjustmen t: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplie
The measure of the degree to which the particular model differs from the saturated model for the data set. Explicitly in terms of the likelihoods of the two models can be defined a
Suppose that $4 million is available for investment in three projects. The probability distribution of the net present value earned from each project depends on how much is invest
The method of displaying the geographical variability of the disease on maps using different colors, shading, etc. The logic is not new, but the arrival of computers and computer g
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