Abstract: The work's objective is to assess how well the classification techniques of logistic regression and support vector machine predict handwritten digits. A Digit dataset with 985 records is ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Space complexity of machine learning algorithms is the amount of memory or storage an algorithm requires for its successful execution. This becomes one of the important metrics of concern since it ...

In the subject of machine learning, it is essential to comprehend regression algorithms. Ten fundamental regression algorithms are introduced in this tutorial, which serves as the foundation for many ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Psychrophilic enzymes are a class of macromolecules with high catalytic activity at low temperatures. Cold-active enzymes possessing eco-friendly and cost-effective properties, are of huge potential ...

Considering the strong non-linear time-varying behavior of dam deformation, a novel prediction model, called Levy flight-based grey wolf optimizer optimized support vector regression (LGWO-SVR), is ...

We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...

Abstract: Distortion correction is a key technology in the filed of machine vision. A radial distortion correction method based on support vector machines for regression is proposed and studied ...