Please explain the bias-variance tradeoff.

Please explain the bias-variance tradeoff.



Answer: The bias-variance tradeoff is essentially a questions of how complex you would like to make your model. The more complex your model, the more likely you model can vary based on the sample of data. This would be high variance and you could be overfitting your model. While a simpler model, reduces the likelihood of this, it increases the chance of you underfitting your model and making it bias towards the features selected for your model.

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