Why might it be important to consider interaction effects in a Multiple Linear Regression model?
- It captures complex relationships
- It increases accuracy independently
- It reduces bias
- It simplifies the model
Considering interaction effects is essential to capture complex relationships between variables that might not be apparent when considering each variable separately.
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