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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.
The Null Hypothesis - H0: There is autocorrelation The Alternative Hypothesis - H1: There is no autocorrelation Rejection Criteria: Reject H0 (n-s)R 2 > = (1515 - 4) x (0.
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The alternative process to make use of the chi-squared statistic for assessing the independence of the two variables forming a two-by-two contingency table particularly when expect
Cartogram : It is the diagram in which descriptive statistical information is displayed on the geographical map by the means of shading, different symbols or in some other possibly
Method of moments is the procedure for estimating the parameters in a model by equating sample moments to the population values. A famous early instance of the use of the proced
Assume that a population is normally distributed with a mean of 100 and a standard deviation of 15. Would it be unusual for the mean of a sample of 20 to be 115 or more?
Odds ratio is the ratio of the odds for the binary variable in two groups of the subjects, such as, males and females. If the two possible states of variable are labeled as 'succe
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
This is the powerful visualization tool for studying how the response relies on an explanatory variable given the values of other explanatory variables. The plot comprises of a num
It is the multivariate normal random vector which satisfies certain conditional independence suppositions. This can be viewed as a model framework which contains a wide range of st
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