Hill-climbing algorithm, Advanced Statistics

Assignment Help:

Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizing some numerical index of the clustering. Since it is not possible to consider every partition of n individuals into g groups (because of the enormous number of the partitions), the algorithm starts with some given initial partition and considers individuals in turn for moving into the other clusters, creating the move if it causes an improvement in the value of the clustering index. The procedure is continued until no move of the single individual causes an improvement.


Related Discussions:- Hill-climbing algorithm

Composite sampling, A procedure whereby the collection of multiple sample u...

A procedure whereby the collection of multiple sample units are combined in their entirety or in part, to form the new sample. One or more succeeding measurements are taken on the

Complier average causal effect (cace), Complier average causal effect (CACE...

Complier average causal effect (CACE): The treatment effect amid true compliers in the clinical trial. For the suitable response variable, the CACE is given by the difference in o

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

Band matrix, Band matrix: A matrix which has its non zero elements arrange...

Band matrix: A matrix which has its non zero elements arranged uniformly near to the diagonal, so that aij = 0 if (i - j)> ml or (j - i)> mu where aij are the elements of matrix a

Z-tests, Hello! I am currently in graduate school earning a masters in ment...

Hello! I am currently in graduate school earning a masters in mental health counseling. I am in a stats course at current and we are reviewing z-scores. I am a little lost because

Explain kleiner hartigan trees, Kleiner Hartigan trees is a technique for ...

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

Regression analyze, I do have a data of real gdp for each state and from 20...

I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try

Point scoring, Point scoring is an easy distribution free method which can...

Point scoring is an easy distribution free method which can be used for the prediction of a response which is a binary variable from the observations on several explanatory variab

Greenhouse geissercorrection, Greenhouse geissercorrection is the method o...

Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow t

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