AIF-C01 Question 29
Single answerA retail company wants to predict whether a customer will make a purchase based on their browsing behavior on the website. Which machine learning technique is the most appropriate for this use case?
- A
Regression
- B
Classification
- C
Clustering
- D
Dimensionality Reduction
Show answer and explanation
Correct answer: B
Explanation
The use case involves predicting whether a customer will make a purchase, which is a binary outcome (yes or no). This is a classification problem because the goal is to assign the customer to one of two categories. Regression is used for predicting continuous outcomes, clustering is for grouping data points, and dimensionality reduction is for simplifying datasets, making them inappropriate for this scenario.
- A. Incorrect.
Regression is typically used for predicting continuous numerical values, such as sales or temperatures, and is not appropriate for predicting a categorical outcome like whether a customer will make a purchase (yes or no).
- B. Correct.
Classification is the correct choice as it is used to predict categorical outcomes, such as whether a customer will make a purchase (yes or no).
- C. Incorrect.
Clustering is used to group data points into clusters based on their similarities without predefined labels. This is unsuitable for predicting a specific outcome like a purchase decision.
- D. Incorrect.
Dimensionality Reduction is used to reduce the number of features in a dataset while retaining as much information as possible. It is not directly applicable to making predictions in this scenario.