Unsupervised Machine Learning Clustering by Waggoner Philip (16 results)
Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Condition: New. 2021. Paperback. . . . . .
Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Paperback. Condition: Brand New. 75 pages. 8.94x5.91x0.28 inches. In Stock.
Language: English
Published by Cambridge University Press 2020-10-31, 2020
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Language: English
Published by CAMBRIDGE, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Condition: New. 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 addi.
Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
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Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
- Print on Demand
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Condition: New. Print on Demand pp. 75.
Language: English
Published by Cambridge University Press, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
- Print on Demand
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Language: English
Published by Cambridge University Press, Cambridge, 2021
Series: Book 8 of 16 - Elements in Quantitative and Computational Methods for the Social Sciences
- Softcover
- Print on Demand
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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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
