Early draft of our “Feature Engineering and Selection” book

By Max Kuhn

model_process.png

(This article was first published on Blog – Applied Predictive Modeling, and kindly contributed to R-bloggers)

Kjell and I are writing another book on predictive modeling, this time focused on all the things that you can do with predictors. It’s about 60% done and we’d love to get feedback. You cna take a look at http://feat.engineering and provide feedback at https://github.com/topepo/FES/issues.

The current TOC is:

  1. Introduction
  2. Illustrative Example: Predicting Risk of Ischemic Stroke
  3. A Review of the Predictive Modeling Process
  4. Exploratory Visualizations
  5. Encoding Categorical Predictors
  6. Engineering Numeric Predictors
  7. Detecting Interaction Effects (these later chapters are not finished yet)
  8. Flattening Profile Data
  9. Handling Missing Data
  10. Feature Engineering Without Overfitting
  11. Feature Selection
To leave a comment for the author, please follow the link and comment on their blog: Blog – Applied Predictive Modeling.

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