Latent Variables
In Data Science, Latent Variables are variables that are not directly observed but are inferred from other variables that are observed. These variables are used to explain the relationships between observed variables and to identify underlying structures in the data. Latent Variables are commonly used in statistical modeling, machine learning, and data mining. They are often used to represent complex concepts or constructs that cannot be directly measured, such as intelligence, personality traits, or customer satisfaction. Latent Variables can be continuous or categorical, and can be modeled using a variety of techniques, including factor analysis, structural equation modeling, and latent class analysis.
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