Prepare

Due: September 17, 2024

prepare
Modified

September 16, 2024

Learning objectives

  • Identify 1-to-1 and 1-to-many transformation methods for encoding numeric predictors
  • Implement transformations for numeric predictors to reduce skewness
  • Introduce basis expansions and splines to incorporate non-linear relationships in predictors
  • Define Generalized Additive Model (GAM) and multivariate adaptive regression spline (MARS) for modeling non-linear relationships
  • Model nonlinear relationships between predictors and the response variable

Preparations

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