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
*For Medical Professionals Only Published in: European Association for Cardio-Thoracic Surgery Impact Factor: IF=3.1 Publication Date: 2024.10.13 Innovations: This study investigates the performance of an in-hospital/30-day mortality risk prediction model using alternative machine learning algorithms (XGBoost) in adults undergoing cardiac surgery. Background: Predictive models are used in international guidelines to determine the most appropriate treatment … Read more
Source: DeepHub IMBA This article is about 6800 words, and it is recommended to read for 10+minutes This article will discuss the techniques to obtain tangible value from the dataset using hypothesis testing, feature engineering, and time series modeling methods. Using statistical tests and machine learning to analyze and predict the performance of solar power … Read more
For most data analysts, regression models are undoubtedly one of the fundamental skills. At the beginning of this century, many investment banks used the application of regression models as a standard for evaluating analysts. For over a decade, regression models have maintained a significant presence in all analyses and predictions. However, in recent years, a … Read more
Previous Review Recommended Article: Complexity of Xi’an Approach Airspace Based on Aircraft and Route Network Recommended Article: Lightweight Massive Spatiotemporal Data Processing and Analysis Service Framework This article was published in “Command Information Systems and Technology”, 2022, Issue 5 Authors:Sui Yuan,Duan Ran,Bai Zheng Citation Format:Sui Yuan, Duan Ran, Bai Zheng. Monitoring Method for Ship Imitation … Read more
Machine Learning Author: louwill Machine Learning Lab Although deep learning is currently dominant, Boosting algorithms represented by XGBoost, LightGBM, and CatBoost still have a wide range of applications. Excluding the unstructured data applications suitable for deep learning, such as images, text, speech, and video, Boosting algorithms remain the first choice for structured data with fewer … Read more
In 2020, the “butterfly effect” was triggered in China’s pharmaceutical industry, with the two wings of this butterfly being the introduction of the MAH system and the initiation of centralized procurement. The MAH system is of great significance in encouraging drug innovation and improving drug quality. According to the MAH system, the drug marketing authorization … Read more