Ensemble Methods for Machine Learning (Gautam Kunapuli) (Z-Library)

Author： Gautam Kunapuli

This book was never intended to be just a tutorial with step-by-step instructions and cut-and-paste code (although you can use it that way, too). There are dozens of suchfantastic tutorials on the web, and they can get you going on your data set in an instant. Instead, I talk about each new method using an immersive approach inspired by that first machine-learning paper I ever read and refined in college classrooms during my time as a graduate lecturer. I’ve always felt that to understand a technical topic deeply, it helps to strip it down, take it apart, and try to put it back together again. I adopt the same approach in this book: we’ll take ensemble methods apart and (re)create them ourselves. We’ll tweak them and poke them to see how they change. And, in doing so, we’ll see exactly what makes them tick! I hope this book will be helpful in demystifying those technical and algorithmic details and get you into the ensemble mindset, be it for your class project, Kaggle competition, or production-quality application.