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Books on the topic 'Tree of decisions'

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Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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1

Reed, W. J. Planting decisions in the face of uncertainty. Vancouver, B.C: Forest Economics and Policy Analysis Research Unit, University of British Columbia, 1991.

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2

Alsolami, Fawaz, Mohammad Azad, Igor Chikalov, and Mikhail Moshkov. Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-12854-8.

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3

Gladwin, Christina. Ethnographic decision tree modeling. Newbury Park: Sage, 1989.

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4

Gladwin, Christina H. Ethnographic decision tree modeling. Newbury Park: Sage, 1989.

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5

Ken, Friedman. The decision tree: A novel. Rainier, Wash: Heart Pub., 1996.

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6

Euler, Bryan L. EDDT: Emotional Disturbance Decision Tree. Lutz, FL: Psychological Assessment Resources, 2007.

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7

Kustra, Rafal. Soft decision trees. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1999.

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8

Grąbczewski, Krzysztof. Meta-Learning in Decision Tree Induction. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00960-5.

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9

Authority, Financial Services. Stakeholder pensions decision trees. London: Financial Services Authority, 2000.

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10

Association, American Bankers. Analyzing financial statements: A decision tree approach. Washington, D.C: American Bankers Association, 2013.

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11

Barros, Rodrigo C., André C. P. L. F. de Carvalho, and Alex A. Freitas. Automatic Design of Decision-Tree Induction Algorithms. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14231-9.

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12

Authority, Financial Services. Stakeholder Pensions and Decision Trees. London: Financial Services Authority, 2000.

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13

Medical conditions and massage therapy: A decision tree approach. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins Health, 2010.

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14

Lloréns, Ximo. Las tres decisiones de J.B. Poquelín. Mérida: Editora Regional de Extremadura, 1991.

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15

service), SpringerLink (Online, ed. Average Time Complexity of Decision Trees. Berlin, Heidelberg: Springer-Verlag GmbH Berlin Heidelberg, 2011.

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16

Chikalov, Igor. Average Time Complexity of Decision Trees. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22661-8.

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17

Dahan, Haim, Shahar Cohen, Lior Rokach, and Oded Maimon. Proactive Data Mining with Decision Trees. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0539-3.

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18

1934-, Helveston Eugene M., ed. Strabismus: A decision making approach. St. Louis: Mosby, 1994.

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19

Kozak, Jan. Decision Tree and Ensemble Learning Based on Ant Colony Optimization. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-93752-6.

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20

Daniel, Muchnik. Tres países, tres destinos: Argentina frente a Australia y Canadá. Buenos Aires: Grupo Editorial Norma, 2003.

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21

Z, Maimon Oded, ed. Data mining with decision trees: Theroy and applications. Singapore: World Scientific, 2008.

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22

Kretowski, Marek. Evolutionary Decision Trees in Large-Scale Data Mining. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21851-5.

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23

Moshkov, Mikhail. Comparative Analysis of Deterministic and Nondeterministic Decision Trees. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41728-4.

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24

Kalles, D. Decision trees and domain knowledge in pattern recognition. Manchester: UMIST, 1994.

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25

Junhai, Zhai, ed. Ji yu bu que ding xing de jue ce shu gui na. Beijing: Ke xue chu ban she, 2012.

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26

Mora y Palomar, Enrique de la, 1907-, ed. Enrique de la Mora: Tres obras decisivas. México, D.F: Consejo Nacional para la Cultura y las Artes, Dirección General de Publicaciones, 2000.

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27

Cole, Forrest. Scratchings record of decision. Ketchikan, AK: U.S. Dept. of Agriculture, Forest Service, Alaska Region, Tongass National Forest, 2007.

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28

Levine, Phillip B. The impact of social policy and economic activity throughout the fertility decision tree. Cambridge, MA: National Bureau of Economic Research, 2002.

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29

Drechsler, Rolf. Binary decision diagrams: Theory and implementation. Boston: Kluwer Academic Publishers, 1998.

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30

Margineantu, Dragos D. Learning decision trees for loss minimization in multi-class problems. [Corvallis, OR: Oregon State University, Dept. of Computer Science, 1999.

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31

Sherk, Murray Wayne. Linear and arbitrary predicates in decision trees for element distinctness. Toronto: University of Toronto, Dept. of Computer Science, 1986.

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32

Ellrod, Gary P. A decision tree approach to clear air turbulence analysis using satellite and upper air data. Washington, D.C: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1989.

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33

Ray, Patrick A. Confronting climate uncertainty in water resources planning and project design: The decision tree framework. Washington, DC: World Bank Group, 2015.

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34

Goetz, Thomas. The decision tree: How to make better choices and take control of your health. New York, NY: Rodale, 2011.

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35

Lbov, G. S. Ustoĭchivostʹ reshai͡ushchikh funkt͡siĭ v zadachakh raspoznavanii͡a obrazov i analiza raznotipnoĭ informat͡sii. Novosibirsk: Izd-vo In-ta matematiki, 2005.

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36

Saaty, Thomas L. The hierarchon: A dictionary of hierarchies. Pittsburgh: Expert Choice, 1992.

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37

Saaty, Thomas L. The hierarchon: A dictionary of hierarchies. Pittsburgh, PA: Expert Choice, 1996.

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38

The decision tree: Taking control of your health in the new era of personalized medicine. Emmaus, Pa: Rodale, 2010.

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39

Magyary, Diane Louise. Children with ADHD: A manual with decision tree and clinical path, for health care professionals. Seattle, Wash: School of Nursing, University of Washington, 1999.

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40

Yanuariadi, Tetra. Sustainable land allocation: GIS-based decision support for industrial forest plantation development in Indonesia. Enschede, The Netherlands: ITC, 1999.

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41

Meyers, Patrick, and Tanja Westfall. Struggle in the Willow Tree (Decisions). A P I X International, 1989.

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42

Cherry, T. S. Apple Decisions: The Tree of Good and Evil. T.S. Cherry, 2017.

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43

Salguero-Gomez, Roberto, and Marlène Gamelon, eds. Demographic Methods across the Tree of Life. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198838609.001.0001.

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Abstract:

Demography is everywhere in our lives: from birth to death. Demography shapes our daily decisions, as well as the decisions that others make on us (e.g. bank loans, retirement age). Demography is everywhere across the Tree of Life. The universal currencies of demography—survival, development, reproduction, and recruitment—shape the performance of all species, from lions to dandelions. The omnipresence of demography in all things alive and dead, and its multiple applications to better understand the ecology, evolution, and conservation/management of species, allows us to—in principle—apply the wide array of quantitative methods to, for example, bacteria or humans. However, demographic methods to date have remained taxonomically siloed, despite the fact that, to a large extent, they are widely applicable across the Tree of Life. In this book, we walk nonexperts through the ABCs of data collection, model construction, analyses, and interpretation across a wide repertoire of demographic artillery. This book introduces the reader to some of the demographic methods, including abundance-based models, life tables, matrix population models, integral projection models, integrated population models, and individual based models, to mention a few. Through the careful integration of data collection methods, analytical approaches, and applications, clearly guided through fully reproducible R scripts, we provide a state-of-the-art thorough representation of many of the most popular tools that any demographer (or demographically inclined mind) should equip themselves with.

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44

Chikalov, Igor, Mikhail Moshkov, Fawaz Alsolami, and Mohammad Azad. Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions. Springer, 2019.

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45

Metalearning In Decision Tree Induction. Springer International Publishing AG, 2013.

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46

Decision Tree Modeling Course Notes. Sas Inst, 2002.

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47

Randall, William D. Software reusability: A decision tree model. 1988.

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48

Grąbczewski, Krzysztof. Meta-Learning in Decision Tree Induction. Springer, 2016.

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49

Mola, Francesco. Evolutionary Algorithms in Decision Tree Induction. INTECH Open Access Publisher, 2008.

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50

Sinnamon, Roslyn Mary. Binary decision diagrams for fault tree analysis. 1996.

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