Unsupervised Learning

Definition(s)

  • A Machine Learning method in which the learning Algorithm infers categories of similar Documents without any training by Subject Matter Expert(s). Examples of Unsupervised Learning methods include Clustering and Near-Duplicate Detection. 1
  • A kind of machine learning where the objects are not labeled by an exterior source. Instead, the machine learning system organizes the objects based on implicit criteria that it derives. The selection of criteria is a function of the specific learning methods that are employed, the nature of the objects, and the way in which features of the object are represented. Clustering is an example of an unsupervised machine learning method. The goal of unsupervised learning is typically to identify hidden structure in unlabeled data, to summarize key features of the data. 2

Notes

  1. Maura R. Grossman and Gordon V. Cormack, EDRM page & The Grossman-Cormack Glossary of Technology-Assisted Review, with Foreword by John M. Facciola, U.S. Magistrate Judge2013 Fed. Cts. L. Rev. 7 (January 2013).
  2. Herb Roitblat, Search 2020: The Glossary.
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