Gustafson-Kessel algorithm

The Gustafson-Kessel (GK) algorithm is a fuzzy clustering method used to group data points based on their similarities. Unlike simpler algorithms that assume clusters are spherical, GK adapts to clusters of different shapes and sizes by using a matrix to describe each cluster's orientation and scale. It assigns points to clusters with varying degrees of membership, allowing for more flexible and accurate groupings in complex datasets. This approach is especially useful when data clusters are elongated, skewed, or irregular, providing a nuanced analysis of data structure.