Hello, I am Cos Dazhuang!~ Recently, there has been a discussion in the community about the mixed classification tasks using XGBoost and KNN. Today, let’s take this opportunity to talk about the details and points to note, as well as the advantages they each bring~ As usual: If you think the recent articles are good! … Read more
This tutorial showcases the application process and workflow of machine learning algorithms through case studies and code-driven examples, enabling you to master the ability to build scenario modeling solutions and perform effect optimization.This article provides a detailed explanation of the engineering application methods of XGBoost. XGBoost is a powerful boosting algorithm toolkit that is the … Read more
Selected from Medium Translated by Machine Heart Contributors: Liu Tianci, Huang Xiaotian Despite the resurgence and popularity of neural networks in recent years, boosting algorithms still have indispensable advantages in scenarios with limited training sample sizes, shorter training times, and lack of tuning knowledge. This article compares three representative boosting algorithms: CatBoost, LightGBM, and XGBoost, … Read more
Dream Morning Reporting from Aofeisi Quantum Bit | Public Account QbitAI What algorithm is most likely to win prizes in machine learning competitions on Kaggle? You might say: Of course, it’s deep learning. Not really. According to statistics, the most winning algorithms are gradient boosting algorithms like XGBoost. This is strange. Deep learning shines in … Read more
This content is sourced from “Surveying and Mapping Bulletin” 2023, Issue 6, Review No.: GS Jing (2023) 1164. Modeling Surface Reflectance in Near Ultraviolet Using XGBoost Aoyong1, Li Hongli2,3, Zhang Wenjuan3, Qin Meng2,3 1. College of Land Engineering, Chang’an University, Xi’an, Shaanxi 710054;2. College of Earth Sciences and Resources, Chang’an University, Xi’an, Shaanxi 710054;3. Aerospace … Read more
Organized by Machine Heart Author: Jiang Siyuan Recently, ApacheCN has opened the XGBoost Chinese documentation project, which provides installation steps, usage tutorials, and tuning tips related to XGBoost. The project has currently completed 90% of the original English documentation, and Machine Heart briefly introduces this documentation and hopes that readers can help improve it. Chinese … Read more
Top Quantitative Self-Media in the Industry Author: Smith Translated by: Fang’s Mantou 1 Introduction Using machine learning to predict the next period’s price or direction based on stock prices is not new, and it does not yield any meaningful predictions. In this article, we will break down the time series data of a series of … Read more
XGBoost: The Winning Tool in Machine Learning! Hello everyone, I’m Mao Ge! Today, I want to introduce you to a magical tool that often wins championships in machine learning competitions – XGBoost. As a gradient boosting framework, XGBoost has become one of the favorite tools among data scientists due to its powerful performance and efficient … Read more
Background The XGBoost model, known as a powerful “weapon” in machine learning, is widely used in data science competitions and industrial applications. The official XGBoost also provides runnable code for various platforms and environments, such as XGBoost on Spark for distributed training. However, in the official implementation of XGBoost on Spark, there exists an instability … Read more
There are many algorithms in machine learning, but today we will focus on one called XGBoost. This tool is quite a big deal in the data science community, with many experts saying it is fast, accurate, and hassle-free. But don’t be afraid, it may sound fancy, but it’s basically a tool that helps us find … Read more