Nuts and bolts of clustering algorithms

Nuts and bolts of clustering algorithms

  • 26/01/2022
    1:00 pm - 2:30 pm

Course details

statistics seminar | level: beginner | register now
for questions related to this event, contact ugent@flames-statistics.com
affiliation: Ghent University


Abstract

Clustering methods refer to the process of partitioning observations into sub-groups whose units are similar with respect to some similarity or distance measure. Many different research questions require applications of common clustering algorithms (or their modified versions) such as K-means and Hierarchical clustering methods. In this seminar, we are going to review these basic clustering algorithms and present their strengths and limitations. A demonstration of how to generate clusters will be done using the R Software.


Prerequisites

none


Background readings

Roger Peng: Clustering

Andrew Ng: Lecture 13.2 — Clustering | KMeans Algorithm — [ Machine Learning]

Practical Guide to Cluster Analysis in R: Unsupervised Machine Learning (Multivariate Analysis) (Volume 1) 1st Edition. by. Mr. Alboukadel Kassambara (Author)

James, G., Witten, D., Hastie, T., \& Tibshirani, R. (2013). An introduction to statistical learning: with applications in R. Corrected edition. New York: Springer.


Fee

Free


Venue

Online


Instructor

Emmanuel Abatih


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