For clustering similar types of customers based on their purchasing behavior, which type of learning would be most appropriate?
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Semi-Supervised Learning
Unsupervised Learning is the most appropriate for clustering customers based on purchasing behavior. In unsupervised learning, the algorithm identifies patterns and groups data without any predefined labels, making it ideal for clustering tasks like this.
Loading...
Related Quiz
- Which 'V' of Big Data refers to the increasing rate at which data is produced and collected?
- An e-commerce platform is trying to predict the amount a user would spend in the next month based on their past purchases. Which type of learning and algorithm would be most suitable for this?
- You are analyzing customer reviews for a product and want to automatically categorize each review as positive, negative, or neutral. Which NLP task would be most relevant for this purpose?
- Which term refers to the ethical principle where AI systems should be transparent about how they make decisions?
- For datasets with multiple features, EDA often involves dimensionality reduction techniques like PCA to visualize data in two or three _______.