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Risk Prediction Score for 30-Day Mortality After Adult Cardiac Surgery Based on Machine Learning Algorithms

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Risk Prediction Score for 30-Day Mortality After Adult Cardiac Surgery Based on Machine Learning Algorithms

*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

Comparison of Time Series Forecasting Using SARIMA, XGBoost, and CNN-LSTM

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Comparison of Time Series Forecasting Using SARIMA, XGBoost, and CNN-LSTM

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

Will XGBoost Algorithm Replace Linear Models?

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Will XGBoost Algorithm Replace Linear Models?

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

Monitoring Method for Ship Imitation Behavior Based on XGBoost

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Monitoring Method for Ship Imitation Behavior Based on XGBoost

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

Comparison and Tuning of XGBoost, LightGBM, and CatBoost Algorithms

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Comparison and Tuning of XGBoost, LightGBM, and CatBoost Algorithms

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

Reducing Quality Costs Based on Xgboost Algorithm

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Reducing Quality Costs Based on Xgboost Algorithm

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

Summary of Decision Trees, Random Forests, Bagging, Boosting, Adaboost, GBDT, and XGBoost

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Summary of Decision Trees, Random Forests, Bagging, Boosting, Adaboost, GBDT, and XGBoost

Official WeChat account of Tsinghua Big Data Software Team Source: Zhihu This article is about 5000 words long, and it is recommended to read for 5 minutes. This article systematically summarizes the related content about decision trees, random forests, etc. 1、Decision Tree A decision tree is a supervised classification model that essentially selects a feature … Read more

Machine Learning and Bioinformatics: XGBoost Analysis

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Machine Learning and Bioinformatics: XGBoost Analysis

With the continuous development of genetics, breeding, and the increasing advancements in the Human Genome Project and molecular biology, biological data has experienced explosive growth over just a few decades. For example, algorithms such as regression analysis, random forests, and support vector machines in bioinformatics are already quite mature. Recently, while reading literature, I came … Read more

XGBoost Split Point Algorithm Explained

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XGBoost Split Point Algorithm Explained

Introduction The previous article introduced the algorithm principles of XGBoost and introduced the scoring function (objective function) that measures the quality of tree structures. The best split point is selected based on the scoring function before and after the feature split points, but a detailed introduction to the node splitting algorithm was not provided. This … Read more

Comparison of XGBoost and LightGBM for Time Series Prediction

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Comparison of XGBoost and LightGBM for Time Series Prediction

XGBoost and LightGBM are currently very popular tree-based machine learning models, both demonstrating efficient performance. However, they have different characteristics in certain situations. Simple Comparison of XGBoost and LightGBM Training Speed LightGBM has a significant advantage over XGBoost in terms of training speed. This is because LightGBM uses some efficient algorithms and data structures, such … Read more