Frontiers

Disease classification via interpretable machine learning based on multi-center routine coagulation test

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...
Frontiers

Salp swarm-optimized machine learning models for predicting preoperative aortic rupture risk in acute type a aortic dissection patients

Acute Type A aortic dissection (ATAAD) is characterized by acute onset and rapid progression, with aortic rupture due to dissection extension being the primary lethal mechanism. Timely identification ...
Hacker

Stop Waiting: Make XGBoost 46x Faster With One Parameter Change

Walkthroughs, tutorials, guides, and tips. This story will teach you how to do something new or how to do something better. Turn Hours of Training Into Minutes With GPU Acceleration If you’re a ...
IEEE

Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm

Abstract: Decision trees in machine learning achieved satisfactory performance in classification. Decision trees offer the advantage of handling high-dimensional and complexly correlated data through ...
Scientific Research Publishing

Zhang, Y. (2022) Stock Price Prediction Method Based on Xgboost Algorithm. Atlantis Press International BV.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
Scientific Research Publishing

Wu, Y. (2023) Stock Price Prediction Based on Simple Decision Tree Random Forest and XGBoost.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
Visual Studio Magazine

Gradient Boosting Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the gradient boosting regression technique, where the goal is to predict a single numeric value. Compared to ...