Library
Chapter 12

Advanced Models for Tabular Data

Curated summaries of the key literature behind this chapter — the findings, the methods, and how to put them to work.

21 referenced in this chapter

This chapter Library is for Research-to-Production students

R2P students unlock curated summaries of every key paper behind this chapter — the core findings, the methods, and how to apply them — plus resources we keep adding over time.

Greedy Function Approximation: A Gradient Boosting Machine
Jerome H. Friedman (2001)
Random Forests
Leo Breiman (2001)
Random Search for Hyper-Parameter Optimization
James Bergstra and Yoshua Bengio (2012)
Predictive learning via rule ensembles
Jerome H. Friedman and Bogdan E. Popescu (2008)
XGBoost: A Scalable Tree Boosting System
Tianqi Chen and Carlos Guestrin (2016)
plus 16 more references inside
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