Offers researchers and teachers an introduction to clustering, with R code and real data to facilitate interaction with the concepts.
"synopsis" may belong to another edition of this title.
FREE shipping within United Kingdom
Destination, rates & speedsSeller: Speedyhen, London, United Kingdom
Condition: NEW. Seller Inventory # NW9781108793384
Quantity: 1 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 41901849-n
Quantity: Over 20 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9781108793384_new
Quantity: Over 20 available
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 140. Seller Inventory # C9781108793384
Quantity: Over 20 available
Seller: Chiron Media, Wallingford, United Kingdom
Paperback. Condition: New. Seller Inventory # 6666-IUK-9781108793384
Quantity: 10 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 41901849
Quantity: Over 20 available
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 75 pages. 8.94x5.91x0.28 inches. In Stock. This item is printed on demand. Seller Inventory # __110879338X
Quantity: 1 available
Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: new. Paperback. In the age of data-driven problem-solving, applying sophisticated computational tools for explaining substantive phenomena is a valuable skill. Yet, application of methods assumes an understanding of the data, structure, and patterns that influence the broader research program. This Element offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered in this Element, in addition to R code and real data to facilitate interaction with the concepts. Upon setting the stage for clustering, the following algorithms are detailed: agglomerative hierarchical clustering, k-means clustering, Gaussian mixture models, and at a higher-level, fuzzy C-means clustering, DBSCAN, and partitioning around medoids (k-medoids) clustering. Offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered, in addition to R code and real data to facilitate interaction with the concepts. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781108793384
Quantity: 1 available
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: New. 2021. Paperback. . . . . . Seller Inventory # V9781108793384
Quantity: 1 available
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condition: New. Unsupervised Machine Learning for Clustering in Political and Social Research 0.23. Book. Seller Inventory # BBS-9781108793384
Quantity: 5 available