Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

Abstract: Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large ...

Forecasting Sustainable Development Goals (SDG) Scores by 2030: The Sustainable Development Goals (SDGs) set by the United Nations aim to eradicate poverty, protect the environment, combat climate ...

Prior to PILOT, fitting linear model trees was slow and prone to overfitting, especially with large datasets. Traditional regression trees struggled to capture linear relationships effectively. Linear ...

ABSTRACT: This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved Solids (TDS) in wells of the Permian basin, Winkler County, Texas. The ...