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. Blending Ensemble Machine Learning With Python Photo by Nathalie, some rights reserved. Blending is an ensemble machine learning technique that uses a machine learning model to learn how to best combine the predictions from multiple contributing ensemble member models.