XGBoost: A Super Useful Python Library! XGBoost is quite renowned in the machine learning community! It’s particularly useful for data mining and predictions. Why? Because it’s accurate! And it’s fast! Today, I’ll chat with you about XGBoost, ensuring you understand it right away! What is XGBoost? XGBoost, short for Extreme Gradient Boosting, sounds quite mysterious, … 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
XGBoost: The Python Tool for Gradient Boosting! Hello everyone! Today I want to share with you a super powerful tool in the field of machine learning—XGBoost. I still remember when I first participated in a Kaggle competition, I noticed that almost all winning solutions used XGBoost, which sparked my strong interest in it. XGBoost is … Read more
Hello everyone, today let’s talk about XGBoost~ XGBoost (Extreme Gradient Boosting) is particularly suitable for variants of Gradient Boosting Decision Trees. It was proposed by Tianqi Chen in 2016 and has been widely popular in machine learning competitions such as Kaggle. The historical background of XGBoost can be traced back to the Gradient Boosting algorithm, … Read more
Core Points:From Principles to Cases, A Complete Summary of XGBoost! Hello, I am Cos Dazhuang~ Recently, many people have been messaging about XGBoost, feeling it’s very useful but still somewhat unclear. Today, we will clarify it from principles, derivation of formulas, to a practical case at the end, hoping it helps! In simple terms, XGBoost … Read more
Programmers transitioning to AI are following this account👇👇👇 1 Data Exploration and Preprocessing 1.1 Competition Review Background As the world’s largest clean energy source, solar energy is renewable and non-polluting compared to coal and oil; as long as there is sunlight, there is solar energy. Therefore, the utilization of solar energy has been prioritized as … Read more
This article provides an overview of the content: 1. Introduction to CatBoost CatBoost is a machine learning library open-sourced by the Russian search giant Yandex in 2017 and is a type of Boosting algorithm. CatBoost, along with XGBoost and LightGBM, is known as one of the three mainstream tools for GBDT, all of which are … 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
Using the XGBoost algorithm often yields good results in Kaggle and other data science competitions, making it popular among practitioners. This article analyzes the prediction process of the XGBoost machine learning model using a specific dataset and demonstrates the results through visualization, allowing us to better understand the model’s prediction process. As the industrial application … Read more
XGBoost has shone in Kaggle competitions. In previous articles, the principles of the XGBoost algorithm and the XGBoost splitting algorithm were introduced. Most explanations of XGBoost parameters found online only scratch the surface, making it extremely unfriendly for those new to machine learning algorithms. This article will explain some important parameters while referencing mathematical formulas … Read more