Question 51
You are training a spam classifier. You notice that you are overfitting the training data. Which three actions can you take to resolve this problem? (Choose three.)
- A. Get more training examples
- B. Reduce the number of training examples
- C. Use a smaller set of features
- D. Use a larger set of features
- E. Increase the regularization parameters
- F. Decrease the regularization parameters
A. Get more training examples: Why: More training examples can help the model generalize better to unseen data. A larger dataset typically reduces the chance of overfitting, as the model has more varied examples to learn from.
C. Use a smaller set of features: Why: Reducing the number of features can help prevent the model from learning noise in the data. Overfitting often occurs when the model is too complex for the amount of data available, and having too many features can contribute to this complexity.
E. Increase the regularization parameters: Why: Regularization techniques (like L1 or L2 regularization) add a penalty to the model for complexity. Increasing the regularization parameter will strengthen this penalty, encouraging the model to be simpler and thus reducing overfitting.