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

Correlated failure times, Data which occur when failure period is recorded ...

Data which occur when failure period is recorded which are dependent. Such type of data can arise in number contexts, for instance, in epidemiological cohort studies in which th

Multimodal distribution, what is pdf,mean & variance for multimodal distrib...

what is pdf,mean & variance for multimodal distribution?

Extreme values, The biggest and smallest variate values among the sample of...

The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.

Multi co linearity, Multi co linearity is the term used in the regression ...

Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the

Expected monetary value, Ask quesoil company is considering whether or not ...

Ask quesoil company is considering whether or not to bid for an offshore drilling contract. If they bid, the value would be $600m with a 65% chance of gaining the contract. The com

Gllamm, Gllamm is a program which estimates the generalized linear latent ...

Gllamm is a program which estimates the generalized linear latent and mixed models by the maximum likelihood. The models which can be fitted include structural equation models mul

What is statistical inference, What is statistical inference?   Statis...

What is statistical inference?   Statistical inference can be defined as the  method of drawing conclusions from data which are subject to random variations. This is based o

Cluster analysis, Cluster analysis : A set of methods or techniques for con...

Cluster analysis : A set of methods or techniques for constructing a sensible and informative classi?cation of an initially unclassi?ed set of data, using variable values observed

Explain normal approximation, Normal approximation : Normal distributions w...

Normal approximation : Normal distributions which approximate other distributions; such as, a normal distribution with the mean np and variance np(1 - p) which acts as an approxima

Two-phase sampling, Two-phase sampling is the sampling scheme including tw...

Two-phase sampling is the sampling scheme including two distinct phases, in the first of which the information about the particular variables of interest is collected on all the m

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