Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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, ...

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

Stock markets are essential for households for wealth creation and for firms for raising financial resources for capacity ...

Abstract: The paper presents a new framework for complex support vector regression (SVR) as well as Support Vector Machines (SVM) for quaternary classification. The method exploits the notion of ...

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...

ABSTRACT: Forecasting future expected returns out-of-sample is challenging due to some statistical characteristics, such as the stochastic and dynamic nature in the time series. Conventional machine ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

When Valve announced its upcoming Steam Machine hardware last month, some eagle-eyed gamers may have been surprised to see that the official spec sheet lists support for HDMI 2.0 output, rather than ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

ALBUQUERQUE, N.M. – Giving Machines are coming to Cottonwood Mall, allowing people to donate to charities with the push of a button. These machines, supported by The Church of Jesus Christ of ...