latentnie
Latentnie, also known as latent variables or hidden variables, are concepts in statistics, machine learning, and data analysis that refer to variables that are not directly observed but are inferred through other variables that are observed. These variables are "latent" in the sense that they are not directly measured or observed, but their presence is inferred from the relationships between observed variables.
Latent variables are commonly used in various fields, including psychology, sociology, and economics, where direct measurement
In machine learning, latent variables are used in models such as latent Dirichlet allocation (LDA) for topic
The study of latent variables involves techniques such as factor analysis, structural equation modeling, and Bayesian
In summary, latent variables are unobserved constructs that are inferred from observed data. They play a crucial