AI-900 Question 106
Single answerA retail company wants to use machine learning to predict future sales based on historical data. They are considering whether to use supervised or unsupervised learning for this task. Which approach should they choose, and why?
- A
Supervised learning, because it uses labeled data to train a model for prediction tasks.
- B
Supervised learning, because it identifies hidden patterns in unlabeled data.
- C
Unsupervised learning, because it uses labeled data to train a model for prediction tasks.
- D
Unsupervised learning, because it identifies hidden patterns in unlabeled data.
Show answer and explanation
Correct answer: A
Explanation
Supervised learning is the correct choice for this scenario because predicting future sales based on historical data is a regression or classification task that requires input-output pairs (labeled data). The model learns from the existing labeled data to predict outcomes for new, unseen inputs. Unsupervised learning, on the other hand, is used for tasks like clustering or dimensionality reduction where labeled data is not available.
- A. Correct.
Correct: Supervised learning is appropriate because the task involves predicting future sales, which requires labeled historical data (input-output pairs) to train the model.
- B. Incorrect.
Incorrect: Supervised learning does not identify hidden patterns in unlabeled data; that is a characteristic of unsupervised learning.
- C. Incorrect.
Incorrect: Unsupervised learning does not use labeled data for prediction tasks. It is used for identifying patterns or clustering in unlabeled data.
- D. Incorrect.
Incorrect: While unsupervised learning identifies hidden patterns in unlabeled data, it is not suitable for prediction tasks like predicting future sales based on historical data.