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Books on the topic 'Datasety'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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1

Geological Survey (U.S.), ed. National elevation dataset. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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2

Bart, Hobijn, and Harvard Business School, eds. The CHAT dataset. Harvard Business School, 2009.

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3

Hutchinson, T. P. The datasets from CBDEA. Rumsby Scientific Publishing, 1993.

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4

1942-, Ullman Jeffrey D., ed. Mining of massive datasets. Cambridge University Press, 2012.

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5

Geological Survey (U.S.), ed. National land cover dataset. U.S. Dept. of the Interior, U.S. Geological Survey, 2000.

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6

Geological Survey (U.S.), ed. The National Hydrography Dataset. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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7

Slayton, Emma, and Julia Bauder. Who Creates Datasets, and How? SAGE Publications, Inc., 2022. http://dx.doi.org/10.4135/9781071900871.

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8

Sarang, Poornachandra. Clustering Small to Humongous Datasets. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49094-1.

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9

Milanović, Branko. Dataset - racial tension, volume 6. World Bank, 2005.

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10

Quiñonero-Candela, Joaquin. Dataset shift in machine learning. MIT Press, 2009.

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11

Ravindra Babu, T., M. Narasimha Murty, and S. V. Subrahmanya. Compression Schemes for Mining Large Datasets. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5607-9.

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12

Drechsler, Jörg. Synthetic Datasets for Statistical Disclosure Control. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0326-5.

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13

Rymer, Thomas E. Data management for large volume datasets. s.n, 1986.

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14

Whelan, Robert, and Hervé Lemaître, eds. Methods for Analyzing Large Neuroimaging Datasets. Springer US, 2025. https://doi.org/10.1007/978-1-0716-4260-3.

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15

Scanlon, S. The UK's networked dataset revolution continues. Library Information Technology Centre, 1993.

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16

García-Álvarez, David, María Teresa Camacho Olmedo, Martin Paegelow, and Jean François Mas, eds. Land Use Cover Datasets and Validation Tools. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90998-7.

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17

Mayeul, Kauffmann, and North Atlantic Treaty Organization. Public Diplomacy Division., eds. Building and using datasets on armed conflicts. IOS Press, 2008.

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18

D, Woodruff Scott, and Climate Monitoring and Diagnostics Laboratory (U.S.). Climate Research Division., eds. Differences within and among surface marine datasets. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Climate Monitoring and Diagnostics Laboratory, Climate Research Division, 1991.

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19

United States. National Aeronautics and Space Administration., ed. Feature isolation and quantification of evolving datasets. National Aeronautics and Space Administration, 1994.

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20

Tarasi, Crina, and Lars Witell. Hierarchical Linear Model Applications to Large Datasets. SAGE Publications Ltd, 2023. http://dx.doi.org/10.4135/9781529667820.

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21

Johnson, Lisa Kaye. Computer analysis of remote sensing and geologic datasets. Washington State University Department of Geology, 1988.

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22

United States. Bureau of Justice Statistics., ed. Linking uniform crime reporting data to other datasets. U.S. Dept. of Justice, Office of Justice Programs, Bureau of Justice Statistics, 2001.

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23

McMullan, Trevor. General information on national and international dataset services. University of Ulster Computer Services, 1992.

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24

Dataset: Population. Washington, DC, 2008. https://doi.org/10.1596/9081.

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25

Skillicorn, David. Understanding Complex Datasets. Chapman and Hall/CRC, 2007. http://dx.doi.org/10.1201/9781584888338.

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26

Wrangling Large Datasets. SAGE Publications, Ltd., 2025. https://doi.org/10.4135/9781036229948.

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27

García Bacete, Francisco. Dataset PSI.2020.12. Universitat Jaume I, 2020. http://dx.doi.org/10.6035/psi.2020.12.

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28

Malhotra, Naresh K. Dataset CD-ROM. Pearson Education, Limited, 2003.

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29

Dataset: Economics & business. Trigon, 1991.

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30

Dataset: Economics & business. Trigon, 1994.

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31

Dataset: Market Access. Washington, DC, 2008. https://doi.org/10.1596/9080.

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32

Graphics of Large Datasets. Springer New York, 2006. http://dx.doi.org/10.1007/0-387-37977-0.

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33

Rajaraman, Anand, Jure Leskovec, and Jeffrey David Ullman. Mining of Massive Datasets. Cambridge University Press, 2020.

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34

Rajaraman, Anand, Jure Leskovec, and Jeffrey David Ullman. Mining of Massive Datasets. Cambridge University Press, 2014.

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35

Rajaraman, Anand, Jure Leskovec, and Jeffrey David Ullman. Mining of Massive Datasets. Cambridge University Press, 2014.

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36

Managing Datasets and Models. Mercury Learning & Information, 2023.

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37

Rajaraman, Anand, and Jeffrey David Ullman. Mining of Massive Datasets. Cambridge University Press, 2011.

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38

Anand Rajaraman Jeffrey David Ullman . Mining of Massive Datasets. Cambridge University, 2014.

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39

Rajaraman, Anand, and Jeffrey David Ullman. Mining of Massive Datasets. Cambridge University Press, 2011.

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40

McLachlan, Geoffrey. Learning from Complex Datasets. Wiley & Sons, Incorporated, John, 2017.

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41

Rajaraman, Anand. Mining of Massive Datasets. Cambridge University Press, 2011.

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42

Managing Datasets and Models. Mercury Learning & Information, 2023.

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43

Managing Datasets and Models. Mercury Learning & Information, 2023.

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44

MINING OF MASSIVE DATASETS. CAMBRIDGE UNIVERSITY PRESS, 2017.

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45

Hooghe, Liesbet, Gary Mark, Tobias Lenz, et al. Constructing the MIA Dataset. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198724490.003.0003.

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Abstract:

Chapter Three introduces the Measure of International Authority (MIA) index on delegation and pooling. The first two sections describe how the authors aggregate scores for individual IO bodies at particular stages of decision making in particular decision areas to estimate delegation and pooling at the level of an international organization. In short, it explains the algorithm that produces delegation and pooling scores. The third section presents descriptive statistics comparing delegation and pooling over time, across IOs, and across decision areas. The chapter concludes with tables that sum

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46

Bielinskienė, Agnė, Loic Boizou, Ieva Bumbulienė, et al. Lithuanian 2-gram dataset. Baltic Institute of Advanced Technology, Vytautas Magnus University, 2019. http://dx.doi.org/10.7220/20.500.12259/223749.

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47

Bielinskienė, Agnė, Loic Boizou, Ieva Bumbulienė, et al. Lithuanian 3-gram dataset. Baltic Institute of Advanced Technology, 2019. http://dx.doi.org/10.7220/20.500.12259/240098.

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48

Bielinskienė, Agnė, Loic Boizou, Ieva Bumbulienė, et al. Lithuanian 1-gram dataset. Baltic Institute of Advanced Technology, Vytautas Magnus University, 2019. http://dx.doi.org/10.7220/20.500.12259/239825.

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49

Bielinskienė, Agnė, Loic Boizou, Ieva Bumbulienė, et al. Lithuanian 4-gram dataset. Baltic Institute of Advanced Technology, Vytautas Magnus University, 2019. http://dx.doi.org/10.7220/20.500.12259/239771.

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50

Dataset: Value of production. Washington, DC, 2008. https://doi.org/10.1596/9082.

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