Blending Ensemble Machine Learning With Python
Blending is an ensemble machine learning algorithm.
It is a colloquial name for stacked generalization or stacking ensemble where instead of fitting the meta-model on out-of-fold predictions made by the base model, it is fit on predictions made on a holdout dataset.
Blending was used to describe stacking models that combined many hundreds of predictive models by competitors in the $1M Netflix machine learning competition, and as such, remains a popular technique and name for stacking in competitive machine learning circles, such as the Kaggle community.
In this tutorial, you will discover how to develop and evaluate a blending ensemble in python.
After completing this tutorial, you will know:
- Blending ensembles are a type of stacking where the meta-model