Abstract
In this chapter we explore the use of unsupervised machine learning, or clustering. We cover distances, dimension reduction techniques, and a variety of unsupervised machine learning methods including hierarchical clustering, k-means clustering, and specialized methods, such as those in the hopach package.
Keywords
- Hierarchical Cluster
- Cluster Center
- Transcription Factor Activity
- Agglomerative Cluster
- Hierarchical Cluster Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2008 Springer Science+Business Media, LLC
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Gentleman, R., Carey, V.J. (2008). Unsupervised Machine Learning. In: Bioconductor Case Studies. Use R!. Springer, New York, NY. https://doi.org/10.1007/978-0-387-77240-0_10
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DOI: https://doi.org/10.1007/978-0-387-77240-0_10
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-77239-4
Online ISBN: 978-0-387-77240-0
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