by using Ward’s agglomerative hierarchical clustering followed by using K -means clustering algorithm to establish final …

is used to preselect the genes. K-means and hierarchical clustering algorithms with different distance metric are … cosine distance metric hierarchical clustering algorithm with k-nearest neighbor has given the best performance measures. …

of hierarchical clustering methodologies the set of economies are segmented. By using the average distance, the study …

hierarchical clustering techniques are used to classify the economies in the sample. By using a correlation-based distance, three …

Hierarchical clustering is a popular method for finding structure in multivariate data, resulting in a binary tree …

interpretable. The authors cut the linkage tree formed while performing the hierarchical clustering of the User-Concerns, at … authors present a method that uses topic modeling techniques to discover a large number of topics and applies hierarchical … clustering to generate a much smaller number of interpretable User-Concerns. These User-Concerns are further compared with topics …