Pattern recognition, Advanced Statistics

Assignment Help:

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.  


Related Discussions:- Pattern recognition

Factor scores, The values assigned to factors for the individual sample uni...

The values assigned to factors for the individual sample units in a factor analysis. The most common approach is "regression method". When the factors are seen as the random variab

Completeness, Completeness : A term applied to a statistic t when there is ...

Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of

Explain johnson-neyman technique, Johnson-Neyman technique:  The technique ...

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

Data fusion, The act of combining data from heterogeneous sources with the ...

The act of combining data from heterogeneous sources with the intent of extracting information that would not be available for any single source in isolation. An example is the com

Generalized additive model, The linear component ηi, de?ned just in the tra...

The linear component ηi, de?ned just in the traditional way: η i = x' 1 A monotone differentiable link function g that describes how E(Yi) = µi is related to the linear compon

Blinder oaxaca method, Blinder Oaxaca method: A method or technique used f...

Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the

Expected-utility maximizer, There are two periods. You observe that Jack co...

There are two periods. You observe that Jack consumes 100 apples in period t = 0, and 120 apples in period t = 1. That is, (c 0 ; c 1 ) = (100; 120) Suppose Jack has the util

Extreme value distribution, The probability distribution, f (x), of largest...

The probability distribution, f (x), of largest extreme can be given as    The location parameter, α is the mode and β is the scale parameter. The mean, variance skewn

Explain regression through the origin, Regression through the origin : In s...

Regression through the origin : In some of the situations a relationship between the two variables estimated by the regression analysis is expected to pass by the origin because th

Sequencing problem, when there is tie in sequencing then what we do

when there is tie in sequencing then what we do

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd