Ensemble Methods in Machine Learning(으)로 돌아가기
Coursera Project Network의 Ensemble Methods in Machine Learning 학습자 리뷰 및 피드백
강좌 소개
In this 2-hour long project-based course, you will learn how to implement various ensemble techniques and use it in machine learning. Ensemble models in machine learning combine the decisions from multiple models to improve the overall performance, The main causes of error in learning models are due to noise, bias and variance, Ensemble methods help to minimize these factors.
필터링 기준:
Ensemble Methods in Machine Learning의 1개 리뷰 중 1~1
교육 기관: Michael F
•2021년 12월 22일
This project walks through basic usage of scikit-learn's ensemble models. Their use is demonstrated both as stand alone models and as layers in a heterogeneous stacking model. The presentation was perfect for me because I knew the theory behind these models but not so much the scikit-learn usage. I strongly advise reading about bagging, boosting, etc. before doing the project, if you don't already have a theoretical background.
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