Clustering is an example of unsupervised machine learning, meaning that you do not know ahead of time what groups you are looking for — you want the algorithm to find those groups for you.

In machine learning, typically non-linear regression techniques are used. Examples of nonlinear regression algorithms include gradient descent, Gauss-Newton, and the Levenberg-Marquardt methods.

In materials science, substances are often classified based on defining factors such as their elemental composition or ...

Next, we will consider the development of machine learning pipelines for small-to-medium datasets on a single node. Finally, we will survey some of the solutions available for leveraging cluster ...

A Tokyo Tech study introduced a machine learning-powered clustering model that incorporates both basic features and target properties, successfully grouping over 1,000 inorganic materials.

Although machine learning methods can readily learn complex nonlinear relationships, ... and four classification methods (logistic regression, support vector machines, random forest, ... Improved ...