The Southern Maryland Chronicle on MSN

How are QA teams using machine learning to predict test failures in real time?

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Mr.Chongwei Shi Enhances Genomic Analysis Through Signal Processing and Machine Learning Integration for Gene Identification

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...
Frontiers

Support vector machine-based classification of bulimia nervosa using diffusion tensor imaging

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...
IEEE

A Novel Ensemble Method Based on Support Vector Dynamic Learning Neural Network for Breast Cancer Diagnosis

Abstract: To improve the accuracy of breast cancer diagnosis and reduce examination costs, a novel ensemble learning method called support vector dynamic learning neural network (SVDL) is proposed in ...
ascopubs.org

Development of a Machine Learning Model for Aspyre Lung Blood: A New Assay for Rapid Detection of Actionable Variants From Plasma in Patients With Non–Small Cell Lung Cancer

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...
Visual Studio Magazine

Linear Support Vector Regression Using C# with Particle Swarm Training

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...
Scientific Research Publishing

Wu, Y. and Liu, Y. (2007) Robust Truncated Hinge Loss Support Vector Machines. Journal of the American Statistical Association, 102, 974-983.

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...
Scientific Research Publishing

Huang, X.L., Shi, L. and Suykens, J.A.K. (2014) Support Vector Machine Classifier with Pinball Loss. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 984-997.

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...