Click the blue text to follow us 2023, Issue 2 Nutritional Component Analysis and Hypertension Prediction Based on XGBoost Model Jiang Huai, Tan Lang, Li Shijie, Liu Yu, Wang Junfeng Abstract: Hypertension is a common chronic disease, and early detection and intervention can reduce the risk of complications. Although the onset and development of hypertension … Read more
Click on the above“Beginner’s Guide to Vision” to choose to add a Star Mark or “Top” Important content delivered promptly Introduction The most common application of the Hessian matrix is in the Newton method optimization algorithm, which primarily seeks the extrema of a function where the first derivative is zero. This article provides a clear … Read more
When I first started exploring machine learning algorithms, I was overwhelmed by all the mathematical content. I found that without fully understanding the intuition behind the algorithm, it was difficult to grasp the underlying mathematical principles. Therefore, I tend to favor explanations that break down the algorithm into simpler, more digestible steps. This is what … Read more
XGBoost utilizes a second technique which is second-order optimization, expanding the loss function l(x,y) using a Taylor series expansion. To approximate it to the second order. This is relatively unique in the XGBoost algorithm, differing from the approach of optimizing using gradient descent in GBT, and also different from Adaboost which increases the weights of … Read more
This Issue Selection 2024 Issue 9 Short-Term Wind Power Prediction Model Based on Transform Domain Analysis and XGBoost Algorithm Wang Yongsheng, Li Hailong, Guan Shijie, Wen Caifeng, Xu Zhiwei, Gao Jing DOI: 10.13336/j.1003-6520.hve.20231942 Read Full Text 01Research Background Research Background Under the multiple constraints of energy resources, ecosystems, and socio-economics, global energy security is undergoing … Read more
Introduction Reference code homepage, still the great Julia Silge’s code, who is also a main author of tidymodels. Overall process The original official tutorial URL: https://juliasilge.com/blog/xgboost-tune-volleyball/ Notes 1. Due to poor external data currently, the data used is the test data from the tidytuesdayR package. 2. Tidymodels is an integrated R language machine learning environment … Read more
A simple technique for integrating decision trees involves training trees on subsamples of the training dataset. A subset of rows from the training data can be used to train individual trees known as bagging. When a subset of rows from the training data is also used when calculating each split point, this is referred to … Read more
Click the blue text | Follow us DOI： 10.3969/j.issn.1671-7775.2023.02.003 Open Science (Resource Service) Identification Code (OSID): Citation Format: Wang Tao, He Yao. Multi-objective energy management strategy of fuel cell vehicle based on nonlinear programming and XGBoost [J]. Journal of Jiangsu University (Natural Science Edition), 2023, 44(2): 142-150. Funding Project: National Natural Science Foundation Youth Science … Read more
XGBoost is a powerful and efficient implementation of gradient boosting ensemble algorithms. Configuring the hyperparameters of the XGBoost model can be challenging, often leading to time-consuming and computationally intensive large grid search experiments. Another way to configure the XGBoost model is to evaluate the model’s performance at each iteration of the algorithm during training and … Read more
First Author: Wang Ruoran, Wang Leping Corresponding Author: Xu Jianguo Author Affiliation: West China Hospital, Sichuan University [REF: Wang R, Wang L, Zhang J, He M, Xu J. XGBoost Machine Learning Algorithm Performed Better Than Regression Models in Predicting Mortality of Moderate-to-Severe Traumatic Brain Injury [published online ahead of print, 2022 Apr 14]. World Neurosurg. … Read more