In statistics, single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerative clustering), at each step combining two clusters that contain the closest pair of elements not yet belonging to the same cluster as each other. A drawback of this method is that it tends to produce long thin clusters in which nearby elements of the same cluster have small distances, but elements at opposite ends of a cluster may be much farther from each other than two elements of other clusters. This may lead to difficulties in defining classes that could usefully subdivide the data. (Wikipedia).
Clustering (2): Hierarchical Agglomerative Clustering
Hierarchical agglomerative clustering, or linkage clustering. Procedure, complexity analysis, and cluster dissimilarity measures including single linkage, complete linkage, and others.
From playlist cs273a
Hierarchical Clustering 3: single-link vs. complete-link
[http://bit.ly/s-link] Agglomerative clustering needs a mechanism for measuring the distance between two clusters, and we have many different ways of measuring such a distance. We explain the similarities and differences between single-link, complete-link, average-link, centroid method and
From playlist Hierarchical Clustering
Applied topology 12: Hierarchical clustering and single-linkage clustering
Applied topology 12: Hierarchical clustering and single-linkage clustering Abstract: We describe hierarchical clustering and dendrograms. The particular hierarchical clustering technique we describe is the simplest one, single-linkage clustering. There are many other hierarchical clusteri
From playlist Applied Topology - Henry Adams - 2021
We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of simila
From playlist Data Science in Minutes
Clustering Introduction - Practical Machine Learning Tutorial with Python p.34
In this tutorial, we shift gears and introduce the concept of clustering. Clustering is form of unsupervised machine learning, where the machine automatically determines the grouping for data. There are two major forms of clustering: Flat and Hierarchical. Flat clustering allows the scient
From playlist Machine Learning with Python
Applied topology 13: The problem of chaining in single-linkage clustering
Applied topology 13: The problem of chaining in single-linkage clustering Abstract: We describe the chaining phenomenon, which is a downside of single-linkage clustering. Fancier hierarchical clustering techniques (such as average linkage) are often preferred over single-linkage because t
From playlist Applied Topology - Henry Adams - 2021
From playlist Clustering Algorithms
Alexander Rolle (6/1/20): Stable and consistent density-based clustering
Title: Stable and consistent density-based clustering Abstract: We present a consistent approach to density-based clustering, which satisfies a stability theorem that holds without any distributional assumptions. We first define a 3-parameter hierarchical clustering of a metric probabilit
From playlist ATMCS/AATRN 2020
Statistical Learning: 12.4 Hierarchical Clustering
Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion: https://www.edx.org/course/statistical-learning
From playlist Statistical Learning
John Healy (5/3/21): Practical Clustering and Topological Data Analysis
I will give a topologically biased history of useful and popular clustering from a data science perspective with links to the language of topological data analysis. Another way to phrase that could be: useful topological data analysis from the perspective of a data science practitioner. Th
From playlist TDA: Tutte Institute & Western University - 2021
Hierarchical Clustering | Agglomerative and Divisive Hierarchical Clustering Explained | Edureka
🔥Edureka Data Scientist Course Master Program https://www.edureka.co/masters-program/data-scientist-certification (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") This Edureka tutorial explains Hierarchical Clustering, types of hierarchical clustering, agglomerative and divisive hierarchical clustering with examp
From playlist Data Science Training Videos
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: http://ocw.mit.edu/6-0002F16 Instructor: John Guttag Prof. Guttag discusses clustering. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at
From playlist MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
Yulia Gel (4/28/21): Topological Clustering of Multilayer Networks
Title: Topological Clustering of Multilayer Networks Abstract: Multilayer networks continue to gain significant attention in many areas of study, particularly, due to their high utility in modeling interdependent systems such as critical infrastructures, human brain connectome, and socio-
From playlist AATRN 2021
Unsupervised Learning | Unsupervised Learning Algorithms | Machine Learning Tutorial | Simplilearn
🔥Artificial Intelligence Engineer Program (Discount Coupon: YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=UnsupervisedLearning-D6gtZrsYi6c&utm_medium=Descriptionff&utm_source=youtube 🔥Professional Certificate Program In AI And Machine Learning: https: