Machine Learning
model-complexity
A measure of the capacity of a machine learning model to fit a wide variety of functions.
Expanded definition
Model complexity refers to how flexible a model is in capturing patterns in data. A model with high complexity can fit a large number of functions, which may lead to overfitting, while a model with low complexity might underfit. Balancing model complexity is crucial for achieving good generalization on unseen data.
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