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?
- Supervised Learning with Linear Regression
- Unsupervised Learning with Principal Component Analysis
- Reinforcement Learning with Deep Q-Networks
- Semi-Supervised Learning with K-Nearest Neighbors
Supervised Learning with Linear Regression is appropriate for predicting a continuous target variable (spending amount) based on historical data. Unsupervised learning is not suitable for prediction tasks, reinforcement learning is for sequential decisions, and semi-supervised learning combines labeled and unlabeled data.
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