Difference between revisions of "Mixture Models; Gaussian"
m |
m |
||
| Line 17: | Line 17: | ||
[http://www.google.com/search?q=Gaussian+Mixture+clustering ...Google search] | [http://www.google.com/search?q=Gaussian+Mixture+clustering ...Google search] | ||
| − | * [[AI Solver]] | + | * [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]] |
** [[...cluster]] | ** [[...cluster]] | ||
* [http://en.wikipedia.org/wiki/Mixture_model#Gaussian_mixture_model Mixture model | Wikipedia] | * [http://en.wikipedia.org/wiki/Mixture_model#Gaussian_mixture_model Mixture model | Wikipedia] | ||
Revision as of 21:33, 12 July 2023
YouTube search... ...Google search
- AI Solver ... Algorithms ... Administration ... Model Search ... Discriminative vs. Generative ... Optimizer ... Train, Validate, and Test
- Mixture model | Wikipedia
a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. The following are examples described in Wikipedia:
- A financial model
- House prices
- Topics in a document
- Handwriting recognition
- Assessing projectile accuracy (a.k.a. circular error probable, CEP)
- Direct and indirect applications
- Predictive Maintenance
- Fuzzy image segmentation
Parameter estimation and system identification
- Expectation maximization (EM)
- Markov chain Monte Carlo
- Moment matching
- Spectral method
- Graphical Methods
- Other methods
- A simulation
