MLS-C01 Question 139
Single answerA retail company wants to predict the total sales for the next quarter based on historical sales data. Which type of machine learning model is most appropriate for this use case?
- A
Classification
- B
Regression
- C
Clustering
- D
Recommendation
Show answer and explanation
Correct answer: B
Explanation
The task of predicting total sales for the next quarter involves forecasting a continuous numeric value based on historical data. Regression models are specifically designed to handle such tasks, making them the most appropriate choice in this scenario.
- A. Incorrect.
Classification is used for predicting categorical outputs, such as labels or classes (e.g., determining whether an email is spam or not). It is not suitable for predicting continuous values like sales.
- B. Correct.
Regression is used to predict continuous numeric values, such as total sales, house prices, or temperature. This makes it the most appropriate choice for the given scenario.
- C. Incorrect.
Clustering is an unsupervised learning technique used to group data points into clusters based on similarities. It does not predict future values, so it is not suitable for this task.
- D. Incorrect.
Recommendation systems are used to suggest products, services, or content to users based on their preferences or behavior. This is not relevant to predicting sales for a future time period.