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. This model ...

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.

Novel machine learning-based cluster analysis method that leverages target material property New cluster analysis technique for grouping materials based on both basic features and targeted properties ...

Learning Vector Quantization, aka LVQ (for both classification and regression) Support Vector Machines, aka SVM (for binary classification) Random Forests, a type of “bagging” ensemble ...

Support vector machine is a robust supervised learning method for classification and regression problems. In a classification problem, one can imagine that the data exist in a multidimensional space, ...