How can EDA techniques help in detecting multicollinearity in a dataset?
- By applying dimensionality reduction techniques to the dataset
- By computing the eigenvalues of the correlation matrix
- By fitting a linear regression model to the dataset
- By generating scatterplots and calculating correlation coefficients between variables
EDA techniques, such as generating scatterplots and calculating correlation coefficients between variables, can help in detecting multicollinearity in a dataset. High correlation between predictor variables is an indication of multicollinearity.
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