SASInstitute A00-406 : SAS® Viya® Supervised Machine Learning Pipelines

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SASInstitute A00-406 Exam Syllabus Topics:

SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

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

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

2. What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?

A) They combine multiple models to improve predictive performance.
B) They are simple and easy to interpret.
C) They require minimal data preprocessing.
D) They are not suitable for large datasets.

3. When building a deep learning neural network, what is the purpose of the activation function in each neuron?

A) To initialize the model
B) To define the learning rate
C) To introduce non-linearity
D) To control the number of hidden layers

4. In reinforcement learning, what is the agent's objective?

A) To learn from labeled data
B) To generate synthetic data
C) To maximize a cumulative reward over time
D) To make predictions

5. When deploying a model, what is "model explainability"?

A) The time it takes to make predictions
B) The process of data preprocessing
C) The simplicity of the model
D) The capability to interpret and understand the model's decisions and predictions

Solutions: