You're reading from scikit-learn Cookbook - Second Edition

Product typeBook

Published inNov 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781787286382

Edition2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1)

Trent Hauck

Assessing cluster correctness

We talked a little bit about assessing clusters when the ground truth is not known. However, we have not yet talked about assessing k-means when the cluster is known. In a lot of cases, this isn't knowable; however, if there is outside annotation, we will know the ground truth or at least the proxy sometimes.

Getting ready

So, let's assume a world where we have an outside agent supplying us with the ground truth.

We'll create a simple dataset, evaluate the measures of correctness against the ground truth in several ways, and then discuss them:

from sklearn import datasets
from sklearn import cluster

blobs, ground_truth = datasets.make_blobs(1000, centers=3,cluster_std=1.75)

...

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scikit-learn Cookbook - Second Edition

Published in: Nov 2017Publisher: PacktISBN-13: 9781787286382

Author (1)

Trent Hauck

Trent Hauck is a data scientist living and working in the Seattle area. He grew up in Wichita, Kansas and received his undergraduate and graduate degrees from the University of Kansas. He is the author of the book Instant Data Intensive Apps with pandas How-to, Packt Publishing—a book that can get you up to speed quickly with pandas and other associated technologies.
Read more about Trent Hauck

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