Filling gaps in data sets or identifying outliers—that's the domain of the machine learning algorithm TabPFN, developed by a ...

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.

For another, supervised-learning algorithms work best with balanced data sets—in other words, ones that have an equal number of examples of what it’s looking for and what it can ignore.

Deep learning defined. Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem ...

Machine-learning algorithms often take the form of a neural network, a large set of simple computing elements, or neurons, that communicate via connections between them that vary in strength, or ...

Machine learning, a field of artificial intelligence (AI), ... The model uses parameters built in the algorithm to form patterns for its decision-making process.