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.

Machine learning gets a lot of buzz. The two most talked about classes of algorithms are classification and clustering. Classification is assigning things a label.

In materials science, substances are often classified based on defining factors such as their elemental composition or crystalline structure. This classification is crucial for advances in materials ...

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.