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Machine Learning With Go

You're reading from  Machine Learning With Go

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781785882104
Pages 304 pages
Edition 1st Edition
Languages

Table of Contents (11) Chapters

Preface 1. Gathering and Organizing Data 2. Matrices, Probability, and Statistics 3. Evaluation and Validation 4. Regression 5. Classification 6. Clustering 7. Time Series and Anomaly Detection 8. Neural Networks and Deep Learning 9. Deploying and Distributing Analyses and Models 10. Algorithms/Techniques Related to Machine Learning

Understanding clustering model jargon

Clustering is quite unique and comes with it's own set of terms, which are shown below. Keep in mind that the following list is only a partial list as there are many different types of clustering with corresponding jargon:

  • Clusters or groups: Each of these clusters or groups is a collection of data points into which our clustering technique organizes our data points.
  • Intra-group or intra-cluster: Clusters resulting from clustering can be evaluated using a measure of similarity between data points and other data points in the same resulting cluster. This is called intra-group or intra-cluster evaluation and similarity.
  • Inter-groupor inter-cluster: Clusters resulting from clustering can be evaluated using a measure of dissimilarity between data points and other data points in other resulting clusters. This is called inter-group or inter...
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