r/MachineLearning - [P] Feature Engineer Optimization in HyperparameterHunter 3.0

A full description of the new feature engineering optimization capabilities can be found in this Medium story. TL;DR: HyperparameterHunter 3.0 adds support for feature engineering optimization. Define different feature engineering steps as normal functions, then let HyperparameterHunter keep track of the steps performed for Experiments, so you can optimize them just like normal hyperparameters, and learn from past Experiments automatically. HyperparameterHunter is a scaffolding for ML experimentation and optimization. Run one-off Experiments or perform hyperparameter optimization, and HH automatically saves the model, hyperparameters, data, CV scheme, and now feature engineering steps, along with much more.