Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Machine learning algorithms learn from data to ... implicit biases in machine learning. Automatic classification of pathology and ... Tree, K-Nearest Neighbors, LVQ (Learning ...

When the machine-learning algorithm combines the various kinds of metadata in its decisions, it can spot some 90 percent of cables that are classified, with a false positive rate of just 11 percent.

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

The system is structured around a client-server architecture designed to provide scalability, remote accessibility, and ...

ADELPHI, Md.-- Army researchers discovered a way to quickly get information to Soldiers in combat using new machine learning techniques. The algorithms will play a significant role in enhancing ...

The full dataset contained 2,523 compounds and included compounds with both senolytic and non-senolytic properties so as not to bias the machine-learning algorithm.

Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants ...