Pursuit Regression (6 results)

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  • Language: Chinese

    Published by China Yanshi Press, 2012

    7802509769 / 9787802509764

    • Softcover

    Seller: liu xing, Nanjing, JS, Chinaliu xing

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    paperback. Condition: New. Paperback. Pub Date: October 2012 Language: Chinese in Publisher: China Yanshi Press pursue reunification is a veteran Internet writer Gideon blog anthology. Just as the title referred to. this is a book about the pursuit of reunification. Person's life seems to be looking for life. search for a spiritual home that can settle their own physical and mental. Some people find some people did not find. Some people seem to have found. and eventually they found themselves did not have to meet. Higu.…

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    paperback. Condition: New. Paperback. Pub Date: 2020-01-01 Pages: 320 Language: Chinese Publisher: China Water Conservancy and Hydropower Press. Projection Pursuit Regression of Complex Systems Non-Assumption Modeling Technology and Application Examples Aiming at the high-dimensionality and hybridity of complex systems. etc. Characteristics. starting from the perspective of exploratory data analysis (EDA) methods. the basic principles of projection pursuit (PP) are introduced in detail. and the focus is on the use of p.…

  • Language: English

    Published by Omniscriptum Apr 2026, 2026

    6134609153 / 9786134609159

    • Softcover
    • Print on Demand

    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 72 pp. Englisch.

  • Language: English

    Published by Omniscriptum, 2026

    6134609153 / 9786134609159

    • Softcover
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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In statisticsprojection pursuit regression (PPR) is a statistical model developed byJerome H. Friedman and Werner Stuetzle which is an extension of additivemodels. This model adapts the additive models in that it first projectsthe data matrix of explanatory variables in the optimal direction beforeapplying smoothing functions to these explanatory variables. The modelconsists of linear combinations of non-linear transformations of linearcombinations of explanatory variables. Both projection pursuitregression and neural networks models project the input vector onto aone-dimensional hyperplane and then apply a nonlinear transformation ofthe input variables that are then added in a linear fashion. Thus bothfollow the same steps to overcome the curse of dimensionality. The maindifference is that the functions fj being fitted in PPR can be differentfor each combination of input variables and are estimated one at a timeand then updated with the weights, whereas is NN these are all specifiedupfront and estimated simultaneously.…

  • Language: English

    Published by OmniScriptum, 2026

    6134609153 / 9786134609159

    • Softcover
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    Seller: preigu, Osnabrück, Germanypreigu

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    Taschenbuch. Condition: Neu. Projection Pursuit Regression | Statistics, Statistical Model, Explanatory Variable, Gauss-Newton | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786134609159 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

  • Language: English

    Published by Omniscriptum Apr 2026, 2026

    6134609153 / 9786134609159

    • Softcover
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    Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In statisticsprojection pursuit regression (PPR) is a statistical model developed byJerome H. Friedman and Werner Stuetzle which is an extension of additivemodels. This model adapts the additive models in that it first projectsthe data matrix of explanatory variables in the optimal direction beforeapplying smoothing functions to these explanatory variables. The modelconsists of linear combinations of non-linear transformations of linearcombinations of explanatory variables. Both projection pursuitregression and neural networks models project the input vector onto aone-dimensional hyperplane and then apply a nonlinear transformation ofthe input variables that are then added in a linear fashion. Thus bothfollow the same steps to overcome the curse of dimensionality. The maindifference is that the functions fj being fitted in PPR can be differentfor each combination of input variables and are estimated one at a timeand then updated with the weights, whereas is NN these are all specifiedupfront and estimated simultaneously.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.…