Linear Regression with Many Predictors and Few Observations
Scenario
You fit an ordinary least squares (OLS) linear regression with 500 predictors (features) and 600 observations (rows).
Questions
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What issue is likely to occur?
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Why does it happen?
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How can L1 regularization (Lasso) mitigate it?