Less interpretable methods

Neural networks and ensemble methods like bagging, random forests, and boosting can greatly increase predictive accuracy at the cost of ease of interpretation.

Joshua Loftus
03-28-2021

Trees and forests

Compositional nonlinearity

(not active yet) Slides, notebooks, exercises

Slides for (tree) ensembles ([PDF])

Slides for deep learning ([PDF])

Notebook for ?

Reuse

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Citation

For attribution, please cite this work as

Loftus (2021, March 28). Neurath's Speedboat: Less interpretable methods. Retrieved from http://joshualoftus.com/ml4ds/09-uninterpretable/

BibTeX citation

@misc{loftus2021less,
  author = {Loftus, Joshua},
  title = {Neurath's Speedboat: Less interpretable methods},
  url = {http://joshualoftus.com/ml4ds/09-uninterpretable/},
  year = {2021}
}