Question: In the maximum likelihood estimation approach, why is the more complex model penalized? 1. To avoid overfitting. 2. To increase the likelihood of the data.

In the maximum likelihood estimation approach, why is the more complex model penalized? 1. To avoid overfitting. 2. To increase the likelihood of the data. 3. To ensure the model fits all data points exactly. 4. To prioritize models with the highest number of parameters

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