Скачать с ютуб Hierarchical Clustering - Problem / Complete linkage / KTU Machine learning в хорошем качестве

Hierarchical Clustering - Problem / Complete linkage / KTU Machine learning

#agglomerativeclusteringexample #hierarchicalclustering #machinelearning The agglomerative clustering is the most common type of hierarchical clustering used to group objects in clusters based on their similarity. The algorithm starts by treating each object as a singleton cluster. Next, pairs of clusters are successively merged until all clusters have been merged into one big cluster containing all objects. The result is a tree-based representation of the objects, named dendrogram. In complete-link (or complete linkage) hierarchical clustering, we merge in each step the two clusters whose merger has the smallest diameter. In single-link (or single linkage) hierarchical clustering, we merge in each step the two clusters whose two closest members have the smallest distance.