Your linear regression model has a high bias. What could be the reasons behind this, and how would you try to fix it?
- High variance in data, Address by using more data
- Irrelevant features, Address by using Lasso regression
- Oversimplified model, Address by increasing model complexity
- Too complex model, Address by reducing model complexity
High bias often stems from an oversimplified model that fails to capture the underlying patterns in the data. Increasing model complexity by adding polynomial terms, interaction terms, or more features can reduce bias and help the model better fit the data.
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