You're building a recommendation system without access to labeled data. How would you proceed using unsupervised learning techniques?
- Combining labeled and unlabeled data
- Employing labeled data
- Using clustering methods
- Using reinforcement strategies
Clustering methods are a common approach in Unsupervised Learning to group data based on similarities, suitable for recommendation systems without labeled data.
Loading...
Related Quiz
- For the k-NN algorithm, what could be a potential drawback of using a very large value of k?
- What is the primary difference between the Gini Index and entropy when used in Decision Trees?
- Why might it be important to consider interaction effects in a Multiple Linear Regression model?
- What is the main difference between supervised and unsupervised learning?
- Explain the Variance Inflation Factor (VIF) and its role in detecting multicollinearity.