EDA techniques can help detect ________ in a dataset.
- Data leakage
- Multicollinearity
- Overfitting
- Underfitting
EDA techniques can help detect multicollinearity in a dataset. By examining correlation matrices or scatter plots, we can get a sense of whether predictor variables are correlated with each other, which might indicate multicollinearity. This is an important consideration as multicollinearity can affect the interpretability of some models and can lead to unstable estimates of regression coefficients.
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