## 12.1 Supervised vs. unsupervised learning (1)

• Supervised vs. unsupervised machine learning
• Unsupervised statistical learning: There are inputs but no supervising output; we can still learn about relationships and structure from such data
• Only observe $$X_{i}$$ and try to group them into clusters
• Supervised statistical learning: involves building a statistical model for predicting, or estimating, an output based on one or more inputs
• We observe both features $$x_{i}$$ and the outcome $$y_{i}$$
• Use the model to predict unobserved outcomes $$(y_{i})$$ of units $$i$$ where we only have $$x_{i}$$
• Good analogy: Child in Kindergarden sorts toys (with or without teacher’s input)
• Q: Would you classify topic models supervised or unsupervised ML and why?

### References

Athey, Susan, and Guido W Imbens. 2019. “Machine Learning Methods That Economists Should Know About.” Annu. Rev. Econom. 11 (1): 685–725.
James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning: With Applications in R. Springer Texts in Statistics. Springer.