Is PCA supervised or unsupervised?
Understand the Problem
The question is asking whether Principal Component Analysis (PCA) is a supervised or unsupervised technique in the context of data analysis and machine learning. PCA is typically used for dimensionality reduction and explores relationships in data without label information, suggesting it falls under the category of unsupervised learning.
Answer
unsupervised
The final answer is unsupervised
Answer for screen readers
The final answer is unsupervised
More Information
Principal Component Analysis (PCA) is an unsupervised learning method used for dimensionality reduction that doesn't require labeled data.
Tips
Common mistake: Confusing PCA as supervised because it's often used as a preprocessing step for supervised learning tasks. Remember, PCA itself doesn't involve labels.
Sources
- The web page with info on - GraphPad - graphpad.com
- Is PCA considered a machine learning algorithm? - GeeksforGeeks - geeksforgeeks.org
- Unsupervised Learning — Principal Component Analysis (PCA) - medium.com
Thank you for voting!
