This article is a part of Chapter 10 of the book “Introduction to Machine Learning Basics” (by Huang Haiguang). XGBoost Algorithm XGBoost is a machine learning algorithm based on the Gradient Boosting Decision Tree (GBDT) invented in February 2014 by PhD student Chen Tianqi from the University of Washington. This algorithm not only has excellent … Read more
When companies interview candidates, the interviewers usually include HR, team leaders, and department managers. The process can be divided into two forms. The first form is where the three interviewers interview the candidates separately. The questions may be the same or different, and each interviewer will give a conclusion based on the candidate’s performance. Finally, … Read more
1 Algorithm Overview XGBoost (eXtreme Gradient Boosting) is also a member of the Boosting family. To understand its working principle, we first need to briefly introduce the related concepts of AdaBoost and GBDT. AdaBoost focuses on misclassified samples, increasing the weight of misclassified samples each time to train new classifiers. XGBoost is essentially a GBDT, … Read more
SIGAI Recommendation SIGAI Resource Summary 60% off on courses taught by Teacher Lei Ming XGBoost is a hot algorithm suitable for analyzing abstract data problems, achieving great results in competitions like Kaggle. Although there are many articles introducing the principles and use of XGBoost, few can clearly and thoroughly explain its principles. The goal of … Read more
Quick Start to Machine Learning with Scikit-Learn When it comes to machine learning, many beginners might feel that it’s far from their reach. However, that’s not the case. Today, let’s talk about how to quickly train and evaluate machine learning models using the scikit-learn library in Python. Imagine, just like building blocks, you can create … Read more