The Mean Shift Algorithm
Mean shift is a hierarchical clustering algorithm that assigns data points to a cluster by calculating a cluster's center and moving it towards the mode at each iteration. The mode is the area with the most data points. At the first iteration, a random point will be chosen as the cluster's center and then the algorithm will calculate the mean of all nearby data points within a certain radius. The mean will be the new cluster's center. The second iteration will then begin with the calculation of the mean of all nearby data points and setting it as the new cluster's center. At each iteration, the cluster's center will move closer to where most of the data points are. The algorithm will stop when it is not possible for a new cluster's center to contain more data points. When the algorithm stops, each data point will be assigned to a cluster.
The mean shift algorithm will also determine the number of clusters needed, in contrast...