Sekoitusjakaumat
Sekoitusjakaumat, also known as mixture models, are statistical models that represent the presence of subpopulations within an overall population. In essence, a sekoitusjakauma assumes that the observed data is a combination of several distinct probability distributions, each representing a different subpopulation.
The core idea is that the observed data points are not generated from a single, simple distribution.
A common example is the Gaussian mixture model, where the component distributions are normal (Gaussian) distributions.
Sekoitusjakaumia are widely used in various fields, including machine learning for tasks like clustering and density