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

1. Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?

A) K-Means Clustering
B) Support Vector Machine (SVM)
C) Principal Component Analysis (PCA)
D) Linear Regression

2. What is the primary goal of A/B testing in the context of model deployment?

A) To compare two different versions of a model or strategy to determine which performs better
B) To create synthetic data
C) To assess data quality
D) To evaluate the model's accuracy

3. Which technique is commonly used for feature scaling or normalization in machine learning pipelines?

A) Decision Trees
B) Standardization
C) Principal Component Analysis (PCA)
D) One-Hot Encoding

4. Which of the following is a common technique for handling missing data in a machine learning pipeline?

A) Ignoring missing data
B) Imputing missing values
C) Replacing missing values with zeros
D) Deleting rows with missing data

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

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

Solutions: