Modellkomplexität
Modellkomplexität refers to the degree of intricacy or detail within a model, whether it be a mathematical, computational, or conceptual representation of a system or phenomenon. It is a fundamental concept in various fields, including statistics, machine learning, physics, and economics, as it directly influences a model's ability to capture reality, its interpretability, and its computational cost.
A simple model, often called a "parsimonious" model, has few parameters and makes fewer assumptions. Such models
Conversely, a complex model incorporates a large number of parameters, intricate relationships, or high-dimensional representations. These
The choice of model complexity is a critical decision in model development, often guided by the principle