Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms

By Stan Salvador, Philip Ka-Fai Chan. IEEE International Conference on Tools with Artificial Intelligence, 2004

799 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

From Baby Steps to Leapfrog: How “Less is More” in Unsupervised Dependency Parsing (2010, methodology): “We use an improved10 L method (Salvador and Chan, 2004) to automatically locate this area of diminishing returns.”
Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior (2011, methodology): “In this work, as in [8], we use the mathematical definition of curvature for a continuous functi n as the basis for ur knee definition.”
Group-Based Alternating Direction Method of Multipliers for Distributed Linear Classification (2017, methodology): “To solve the above problem, the L method is adopted in this paper, which can automatically determine a suitable number of clusters from any hierarchical clustering methods [35].”
A framework for delineating biogeographical regions based on species distributions (2010, methodology): “The L-criterion tends to somewhat underestimate the number of optimal clusters in such cases (Salvador & Chan, 2004).”
Multifidelity importance sampling (2016, background): “, [40] for an extensive survey of such techniques.”