AI-900 Question 110
Single answerA retail company wants to build a machine learning model to predict future sales based on past sales data, seasonal trends, and promotional activities. Which type of machine learning approach is the most suitable for this scenario?
- A
Supervised learning
- B
Unsupervised learning
- C
Reinforcement learning
- D
Clustering
Show answer and explanation
Correct answer: A
Explanation
This scenario requires predicting a continuous outcome (future sales), which is a regression problem under supervised learning. Supervised learning uses labeled data to train models to map inputs to outputs, making it the most appropriate approach for this task.
- A. Correct.
Supervised learning is the most suitable approach because the task involves predicting a future value (sales) based on labeled historical data, where the input features (past sales, trends, promotions) are mapped to a target outcome (future sales).
- B. Incorrect.
Unsupervised learning is not suitable in this scenario because it is typically used for tasks like clustering or anomaly detection where there are no labeled outputs to predict.
- C. Incorrect.
Reinforcement learning is not applicable here because it is used for scenarios where an agent learns to make decisions through trial and error to maximize rewards, such as in games or robotics.
- D. Incorrect.
Clustering is a specific unsupervised learning technique used to group similar data points together, but it does not involve predicting a target value such as future sales.