This python package implements k-medoids clustering with PAM and variants of clustering by direct optimization of the (Medoid) Silhouette. It can be used with arbitrary dissimilarites, as it requires ...

In this article we prove two characterizations of the Euclidean ball: (i) the only convex body in ℝ³ such that every normal plane bisects the volume (or surface area) is the Euclidean ball, (ii) the ...

Stroke causes behavioral deficits in multiple cognitive domains and there is a growing interest in predicting patient performance from neuroimaging data using machine learning techniques. Here, we ...

The weighted k-nearest neighbors (k-NN) classification algorithm is a relatively simple technique to predict the class of an item based on two or more numeric predictor variables. For example, you ...

What is Distance Metric Learning? Many machine learning algorithms need a similarity measure to carry out their tasks. Usually, standard distances, like euclidean distance, are used to measure this ...