Explore the five major platforms for developing machine learning models, their features, and how they support AI advancements.

Machine learning plays a pivotal role in the development of autonomous vehicles and robots. In the realm of mechanical ...

Keywords: statistical model selection, assumptions, linear regression, ANOVA, machine learning, homoscedasticity, normality, independence, data transformation, non-parametric tests, robust ...

While building machine learning models is fundamental to today’s narrow applications of AI, there are a variety of different ways to go about realizing the same ends. So-called machine learning ...

Models, uses and limitations Machine learning exercises follow a circular pattern. First, data is prepared and cleaned. Next, a data scientist will select an algorithm to use as the basis for the ...

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.

This fundamental (and quite reasonable) limitation of any machine learning technique is addressed by feature selection: choosing a good set of features upon which to build models.

Donor selection practices for matched unrelated donor (MUD) hematopoietic cell transplantation (HCT) vary, and the impact of optimizing donor selection in a patient-specific way using modern machine ...