Regularisation
Regularization is commonly employed when dealing with anomalies to mitigate their undue impact on predictive models. While regularization may not directly identify outliers, its primary role is to reduce the influence of outliers on the model's results.
Instead of explicitly detecting outliers, it focuses on making the model more robust and less sensitive to extreme data points.
Regularisation types
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Regularisation
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Regularization is commonly employed when dealing with anomalies to mitigate their undue impact on predictive models. While regularization may not directly identify outliers, its primary role is to reduce the influence of outliers on the model's results.
Instead of explicitly detecting outliers, it focuses on making the model more robust and less sensitive to extreme data points.
Regularisation types
Merci pour vos commentaires !