Support Vector Machines (SVMs) represent a robust and versatile class of machine learning algorithms that have significantly shaped the fields of pattern recognition, classification, and regression.

MRI radiomics model uses pituitary scans to accurately predict growth hormone deficiency in children, providing a ...

Unlike conventional sustainability audits, which require time-consuming data collection and hardware deployment, this ...

A machine learning–driven web tool based on 13 standard patient metrics demonstrates strong predictive performance for MASLD, ...

The following six machine learning models were developed to predict ADH upgrade from core needle biopsy: gradient-boosting trees, random forest, radial support vector machine (SVM), weighted K-nearest ...

The researchers identify critical limitations that restrict the full realization of AI’s potential in mine safety. A major ...

This is a preview. Log in through your library . Abstract Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods ...

For years, we believed the Himalayas were a climatic sanctuary—untouched, pristine, and resilient to the turbulence of ...

The support vector machine (SVM) is a popular learning method for binary classification. Standard SVMs treat all the data points equally, but in some practical problems it is more natural to assign ...

Pinecone Systems Inc. is emerging from stealth mode today armed with $10 million in seed funding and a serverless vector database that it says can make machine learning queries much faster and more ...