AIF-C01 Question 28
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 most appropriate for this use case?
- A
Regression
- B
Classification
- C
Clustering
- D
Reinforcement Learning
Show answer and explanation
Correct answer: B
Explanation
The task of predicting whether a customer will make a purchase is a supervised learning problem involving categorical outcomes ('purchase' or 'no purchase'). Classification is the most suitable machine learning technique for this use case, as it is specifically designed for predicting discrete labels based on input features.
- A. Incorrect.
Regression is used for predicting continuous numerical values, such as forecasting sales or predicting house prices. It is not suitable for predicting a binary outcome like whether a customer will make a purchase.
- B. Correct.
Classification is the correct choice because it is used to predict categorical outcomes, such as 'purchase' or 'no purchase' based on input features like browsing behavior.
- C. Incorrect.
Clustering is an unsupervised learning technique used to group similar data points together. It is not suitable for supervised tasks like predicting a purchase outcome.
- D. Incorrect.
Reinforcement Learning involves training agents to make decisions in an environment to maximize rewards. It is not suitable for this scenario, as it does not involve predicting outcomes based on labeled data.