IEEE

Predicting Phenotypes From High-Dimensional Genomes Using Gradient Boosting Decision Trees

Abstract: xsxsGenomic selection (GS) is an emerging technique for predicting unknown phenotypes using genome-wide marker coverage, allowing the use of efficient computational models to select ...
IEEE

Comprehensive Investigation and Comparative Analysis of Machine Learning-Based Small-Signal Modelling Techniques for GaN HEMTs

Abstract: A number of machine learning (ML) algorithm based small signal modeling of Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs) have been reported in literature. However, these ...
Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
The Scientist

The Scientist - Home

This postdoctoral researcher explores how metabolic states, such as after a meal, influence T cell immunity and functional programming.
GitHub

PranavAggarwal422/classical-ml-from-scratch

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C&EN

Harnessing Advanced Machine-Learning Algorithms for Optimized Data Conditioning and Petrophysical Analysis of Heterogeneous, Thin Reservoirs

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GitHub

su-ntu-ctp/6m-data-3.4-Supervised-Learning-Advanced

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Frontiers

Machine Learning Algorithms for Predicting Glycemic Control and Weight Loss Outcomes in GLP-1 Receptor Agonist Users

Machine learning models, particularly tree-based ensemble methods, showed strong potential for predicting treatment response to GLP-1 RA therapy. These findings highlight the value of integrating ...