Powerful 'Trick' to choose right models in Ensemble Learning

I hope you've followed my previous articles on ensemble modeling. In this article, I'll share a crucial trick helpful to build models using ensemble learning. 'How to choose the right models for your ensemble process?' Imagine the following scenario (great, if you can relate to it). You are working on a classification problem and have built 1000 machine learning models. Each of the model gives you an AUC in the range of 0.7 to 0.75 .