Generalized Additive Models (GAM)
A flexible generalization of linear models that allows for non-linear relationships between the independent and dependent variables.
Implications
A flexible statistical model used to describe relationships between variables by allowing for non-linear effects, often used in data analysis to uncover complex patterns and interactions in data, particularly when linear models are insufficient.
Example
Example: A data analyst uses a generalized additive model to predict customer purchasing behavior, allowing for non-linear relationships between variables such as income, age, and marketing exposure.
Related Terms
Different from generalized linear models (GLM), which assume linear relationships between variables, GAMs allow for more flexibility by incorporating smooth, non-linear functions into the model.
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