K-means cluster analysis, Advanced Statistics

Assignment Help:

K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned, if suitable, to a different cluster in an attempt to optimize some predefined numerical criterion that measures in some sense the 'quality' of cluster solution. Several such clustering criteria have been suggested, but the most usually used arise from considering the features of the within groups, between groups and whole matrices of sums of squares and the cross products (W, B, T) which can be described for every partition of the observations into the particular number of groups. The two most ordinary of the clustering criteria developing from these matrices are given as follows

minimization of trace W

minimization of determinant W

The first of these has tendency to produce the 'spherical' clusters, the second to produce clusters that all have same shape, though this will not necessarily be spherical in shape. 

 


Related Discussions:- K-means cluster analysis

Statistical methods with financial applications, The marketing manager of H...

The marketing manager of Handy Foods Ltd. is concerned with the sales appeal of one of the company's present label for one of its products. Market research indicates that supermark

Kaiser''s rule, Kaiser's rule is the  rule frequently used in the principa...

Kaiser's rule is the  rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati

correlation, i will like to submit my project for you to do on chi-square,...

i will like to submit my project for you to do on chi-square, ANOVA, and correlation and simple regression. how can we do this?

General location model, The model for data containing continuous and catego...

The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult

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

Bayesian network, Bayesian network : It is essentially an expert system in ...

Bayesian network : It is essentially an expert system in which the uncertainty is dealt with using the conditional probabilities and Bayes' Theorem. Formally such type of network c

Explain knox''s test, Knox's tests: These tests designed to detect any ten...

Knox's tests: These tests designed to detect any tendency for the patients with a particular disease to form the disease cluster in time and space. The tests are relied on a two-b

Multitrait multi method model (mtmm), Multitrait multi method model (MTMM) ...

Multitrait multi method model (MTMM) is the form of confirmatory factor analysis model in which the different techniques of measurement are used to measure each of the latent vari

Define non linear mapping (nlm), Non linear mapping (NLM ) is a technique f...

Non linear mapping (NLM ) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences

Linear regression, regression line drawn as Y=C+1075x, when x was 2, and y ...

regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual

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