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Hands-On Automated Machine Learning
book

Hands-On Automated Machine Learning

by Sibanjan Das, Umit Mert Cakmak
April 2018
Beginner to intermediate content levelBeginner to intermediate
282 pages
6h 52m
English
Packt Publishing
Content preview from Hands-On Automated Machine Learning

Unsupervised AutoML

When your dataset doesn't have a target variable, you can use clustering algorithms to explore it, based on different characteristics. These algorithms group examples together, so that each group will have examples as similar as possible to each other, but dissimilar to examples in other groups.

Since you mostly don't have labels when you are performing such analysis, there is a performance metric that you can use to examine the quality of the resulting separation found by the algorithm.

It is called the Silhouette Coefficient. The Silhouette Coefficient will help you to understand two things:

  • Cohesion: Similarity within clusters
  • Separation: Dissimilarity among clusters

It will give you a value between 1 and -1, with ...

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Publisher Resources

ISBN: 9781788629898Supplemental Content