AIF-C01 Question 17
Select 1A company is developing an AI solution to predict customer churn based on historical labeled data, cluster customers into groups based on their purchasing behavior, and train a virtual agent to interact with customers by maximizing rewards over time. Which of the following correctly identifies the types of machine learning that should be used for these tasks?
- A
Supervised learning for predicting customer churn, unsupervised learning for clustering customers, and reinforcement learning for training the virtual agent.
- B
Supervised learning for clustering customers, reinforcement learning for predicting customer churn, and unsupervised learning for training the virtual agent.
- C
Unsupervised learning for predicting customer churn, supervised learning for clustering customers, and reinforcement learning for training the virtual agent.
- D
Reinforcement learning for predicting customer churn, unsupervised learning for clustering customers, and supervised learning for training the virtual agent.
Show answer and explanation
Correct answer: A
Explanation
This scenario involves three types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Predicting customer churn uses supervised learning because it requires labeled historical data. Clustering customers into groups based on behavior is a classic unsupervised learning task as it works with unlabeled data to find patterns. Training a virtual agent to interact with customers is a reinforcement learning problem, as it focuses on learning optimal actions to maximize rewards over time.
- A. Correct.
Correct: Predicting customer churn uses supervised learning as it relies on labeled historical data. Clustering customers is an unsupervised learning task as it groups data without labeled output. Training a virtual agent involves reinforcement learning because it focuses on maximizing rewards through trial and error.
- B. Incorrect.
Incorrect: Clustering customers is an unsupervised learning task, not a supervised one. Customer churn prediction uses supervised learning, not reinforcement learning. Training a virtual agent is not an unsupervised learning task.
- C. Incorrect.
Incorrect: Predicting customer churn is a supervised learning task, not an unsupervised one. Clustering customers is unsupervised learning, not supervised. Training a virtual agent uses reinforcement learning, not supervised learning.
- D. Incorrect.
Incorrect: Predicting customer churn is a supervised task, not reinforcement learning. Clustering customers is an unsupervised task, not reinforcement learning. Training a virtual agent involves reinforcement learning, not supervised learning.