In a study published in the journal Information Systems Research, Texas Tech University's Shuo Yu and his collaborators ...

Some studies containing instructions in white text or small font — visible only to machines — will be withdrawn from preprint ...

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

Discover how machine learning is reshaping chemical manufacturing—from optimizing reactions and reducing waste to ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) ...

Maternal mortality is a major public health concern worldwide. It is the number of preventable deaths that occur each year due to pregnancy and childbirth. The research investigates how machine ...

This study uses a dataset with several borrower characteristics to forecast credit risk using Machine learning (ML) and Deep Learning (DL) techniques in addition to statistical methods. With a 98.1% ...

In machine learning, there has long been a trade-off between accuracy and explainability. This drawback has led to the creation of explainable ML libraries such as Shap and Lime which make estimations ...

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property.

It is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. This hard cover book has 738 pages in full colour, ...

Shaw Connolly is obsessed with learning the fate of her sister, who disappeared 16 years ago. She still distributes posters and searches the woods with a cadaver dog.