What are drawbacks of a linear model?

Data Science, AI and ML
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#1

There are a couple of drawbacks of a linear model:

  • A linear model holds some strong assumptions that may not be true in application. It assumes a linear relationship, multivariate normality, no or little multicollinearity, no auto-correlation, and homoscedasticity
  • A linear model can’t be used for discrete or binary outcomes.
  • You can’t vary the model flexibility of a linear model.