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Parth now decides to use only the two most important features, $X_1$ , and $X_2$, in the dataset to predict weekly watch time. Given below is the scatterplot of the two feature values along a representative sample of the dataset. Recall Parth's model was based on ridge regression. From the plot below, how would the model bias be affected if Parth were to use a LASSO regression model instead?

  1. Model bias increases.
  2. Model bias decreases.
  3. Model bias stays the same.
  4. Not enough information to determne
  • 🚩 Edit necessary | 👮 Laplance_Demon | 💬 “Correct Answer is D”

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Model bias measures the expected difference between a model's predictions and the true values of the target variable. Evaluating the bias of any regression model—whether Ridge or LASSO—requires knowing the relationship between the input features and the target variable (in this case, "weekly watch time"). Because the target variable's values are entirely absent from the plot and the problem description, it is impossible to calculate or infer how the model's predictions, and consequently its bias, would change.

 

Therefore, the correct option is D. Not enough information to determine.

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