Skip to Content
Numerical Computing with Python
book

Numerical Computing with Python

by Pratap Dangeti, Allen Yu, Claire Chung, Aldrin Yim
December 2018
Beginner to intermediate
682 pages
18h 1m
English
Packt Publishing
Content preview from Numerical Computing with Python

The elbow method

The elbow method is used to determine the optimal number of clusters in k-means clustering. The elbow method plots the value of the cost function produced by different values of k. As you know, if k increases, average distortion will decrease, each cluster will have fewer constituent instances, and the instances will be closer to their respective centroids. However, the improvements in average distortion will decline as k increases. The value of k at which improvement in distortion declines the most is called the elbow, at which we should stop dividing the data into further clusters.

Evaluation of clusters with silhouette ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Mastering Numerical Computing with NumPy

Mastering Numerical Computing with NumPy

Umit Mert Cakmak, Tiago Antao, Mert Cuhadaroglu

Publisher Resources

ISBN: 9781789953633OtherOtherErrata Page