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最新的 SAS Certified Specialist A00-406 免費考試真題:

1. What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

A) To add more features to the model
B) To increase model complexity
C) To speed up model training
D) To prevent overfitting and reduce model complexity

2. In machine learning, what does "overfitting" refer to?

A) A model that is undertrained and has high bias
B) A model that is unable to make predictions
C) A model that has too much complexity and fits the training data too closely
D) A model that performs well on new, unseen data

3. What is the purpose of hyperparameter tuning in a machine learning pipeline?

A) To train the model
B) To optimize the model's hyperparameters for better performance
C) To select the most important features
D) To evaluate the model's predictions

4. In a machine learning pipeline, what is the purpose of cross-validation?

A) To train multiple models on different subsets of the data to assess generalization
B) To split the dataset into training and testing sets
C) To evaluate the model's performance on new data
D) To visualize the data distribution

5. What is the primary role of a loss function in model training?

A) To visualize the data
B) To measure the difference between predicted and actual values
C) To maximize the model's performance
D) To assess the accuracy of the model

問題與答案：