標題: Titlebook: Grade Models and Methods for Data Analysis; With Applications fo Teresa Kowalczyk,El?bieta Pleszczyńska,Frederick R Book 2004 Springer-Verl [打印本頁] 作者: 候選人名單 時間: 2025-3-21 17:30
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書目名稱Grade Models and Methods for Data Analysis影響因子(影響力)學科排名
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書目名稱Grade Models and Methods for Data Analysis網絡公開度學科排名
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書目名稱Grade Models and Methods for Data Analysis被引頻次學科排名
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書目名稱Grade Models and Methods for Data Analysis讀者反饋
書目名稱Grade Models and Methods for Data Analysis讀者反饋學科排名
作者: 滲透 時間: 2025-3-21 21:17 作者: 使害羞 時間: 2025-3-22 01:25
Univariate Lilliputian Model II, earnings . to female earnings . happened to be convex. This indicated a clear monotone trend: the higher the earnings macrocategory, the stronger the domination of male earnings over female earnings. Departures from convexity were noted for less aggregated data earnings.作者: Spangle 時間: 2025-3-22 08:02 作者: 膽小懦夫 時間: 2025-3-22 11:14
Preliminary concepts of bivariate dependence,meters based on concentration measures (applied e.g., to pairs of conditional distributions). In this way concepts belonging to the Univariate Lilliputian Model (???) supplement and help one to visualize the traditional model of bivariate dependence.作者: 愛了嗎 時間: 2025-3-22 13:22
Book 2004therefore aiming both at researchers, students, as well as applied practitioners. The text is richly illustrated through examples and case studies and includes a short introduction to software implementing grade methods, which can be downloaded from the editors..作者: 愛了嗎 時間: 2025-3-22 19:35
C. Cheniclet,C. Bernard-Dagan,G. Pauly local maxima starting from the original table after the random permutations of its rows and columns, and then selects the highest value of .* as the global maximum (or at least a very good approximation of the global maximum).作者: FRAUD 時間: 2025-3-22 22:58 作者: Manifest 時間: 2025-3-23 04:09 作者: CHARM 時間: 2025-3-23 09:16 作者: 光亮 時間: 2025-3-23 11:59
1434-9922 grade data analysis.Includes supplementary material: .This book provides a new grade methodology for intelligent data analysis. It introduces a specific infrastructure of concepts needed to describe data analysis models and methods. This monograph is the only book presently available covering both 作者: 灌溉 時間: 2025-3-23 15:22 作者: 長處 時間: 2025-3-23 20:57 作者: Condyle 時間: 2025-3-23 22:56
Pathophysiology of Atherosclerosis,meters based on concentration measures (applied e.g., to pairs of conditional distributions). In this way concepts belonging to the Univariate Lilliputian Model (???) supplement and help one to visualize the traditional model of bivariate dependence.作者: MAOIS 時間: 2025-3-24 05:40
978-3-642-53561-1Springer-Verlag Berlin Heidelberg 2004作者: 環(huán)形 時間: 2025-3-24 07:47
Grade Models and Methods for Data Analysis978-3-540-39928-5Series ISSN 1434-9922 Series E-ISSN 1860-0808 作者: 公社 時間: 2025-3-24 13:44 作者: Neolithic 時間: 2025-3-24 16:01 作者: 天然熱噴泉 時間: 2025-3-24 22:59
Zanvil A. Cohn,Ralph M. SteinmanChapter 1 provided a first look at what grade methods do, how they work, why they are useful, and some of their applications. It was stated that grade methods use a different approach to the understanding of data than the traditional (i.e, non-grade) methods. Therefore, to understand grade methods it is important to understand their approach作者: 神刊 時間: 2025-3-25 00:28
The Barley/, (Syn. , InteractionThis chapter presents the ideas introduced in Chapter 2 in a more formal and systematic way. We show how two random variables . and . can be compared and how they can be represented by one variable valued in the interval [0, 1] and therefore called “Lilliputian”. The set of all Lilliputian variables is called the . and denoted ???.作者: MELON 時間: 2025-3-25 04:58
https://doi.org/10.1007/978-1-4613-3894-9We introduce here the extension of ???, called . and denoted ???.作者: 針葉 時間: 2025-3-25 11:32 作者: subordinate 時間: 2025-3-25 12:08 作者: 令人作嘔 時間: 2025-3-25 17:26
https://doi.org/10.1007/978-3-642-48868-9The GradeStat application. has been created using Microsoft Visual C++ with MFC. This data analysis package implements many grade methods.作者: 形上升才刺激 時間: 2025-3-25 21:52
,Grade Data Analysis — A First Look,If you have experience with data analysis, you may have had the following consulting experiences:作者: 乞討 時間: 2025-3-26 01:33
The Grade Approach,Chapter 1 provided a first look at what grade methods do, how they work, why they are useful, and some of their applications. It was stated that grade methods use a different approach to the understanding of data than the traditional (i.e, non-grade) methods. Therefore, to understand grade methods it is important to understand their approach作者: 淺灘 時間: 2025-3-26 05:03
Univariate Lilliputian Model I,This chapter presents the ideas introduced in Chapter 2 in a more formal and systematic way. We show how two random variables . and . can be compared and how they can be represented by one variable valued in the interval [0, 1] and therefore called “Lilliputian”. The set of all Lilliputian variables is called the . and denoted ???.作者: 繁忙 時間: 2025-3-26 09:19
Dependence Lilliputian Model,We introduce here the extension of ???, called . and denoted ???.作者: 吊胃口 時間: 2025-3-26 14:30 作者: 輕率看法 時間: 2025-3-26 17:36 作者: depreciate 時間: 2025-3-26 23:14 作者: Biofeedback 時間: 2025-3-27 04:28 作者: 建筑師 時間: 2025-3-27 08:00 作者: NAV 時間: 2025-3-27 13:10 作者: 藝術 時間: 2025-3-27 16:34 作者: META 時間: 2025-3-27 21:04
Regularity and the number of clusters, curves introduced in Chapter 6. It will be shown that members of a parametrized family of two-dimensional distributions from the Bivariate Lilliputian Model (???)which are based on parabolas are ideally regular data tables (Sections 11.2–11.3).作者: 收集 時間: 2025-3-28 00:54
Inequality measures for multivariate distributions,variate datasets with . sets of records. These measures are easy to percept for those who are familiar with the concepts of the Lorenz Curve and Gini Index which are so important in the univariate case.作者: 搬運工 時間: 2025-3-28 02:20 作者: 旁觀者 時間: 2025-3-28 09:32
Univariate Lilliputian Model II,s, data were ordered according to increasing earnings. For earnings aggregated to four macrocategories, the concentration curve .(. : .) relating male earnings . to female earnings . happened to be convex. This indicated a clear monotone trend: the higher the earnings macrocategory, the stronger the作者: 蛛絲 時間: 2025-3-28 10:45
Asymmetry and the inverse concentration set,ack sufficient precision. It is due to the fact that there are many curves which have the same index value. Problems related to how greatly such curves may differ are discussed in Sec. 5.2. In particular, the boundaries of the smallest region containing all maximal concentration curves with a common作者: 放逐某人 時間: 2025-3-28 14:37
Discretization and regularity,ion of two variables is considered. Due to the formalism used (i.e., grade framework) which is based on concentration indices, the discretization of one random variable can be treated as a particular example of this problem. The grade framework is described in Sec. 6.2.作者: synchronous 時間: 2025-3-28 22:14
Preliminary concepts of bivariate dependence,istributions. Traditional infrastructure (in particular, regression and correlation meaningful for at least interval variables) is completed with parameters based on concentration measures (applied e.g., to pairs of conditional distributions). In this way concepts belonging to the Univariate Lillipu作者: extrovert 時間: 2025-3-29 00:12 作者: 不出名 時間: 2025-3-29 03:18
Cluster analysis based on GCA,escribed in Chapter 6 for pairs of random variables. Although the theoretical background assumes that the data must have the form of two-way probability tables, the method is applicable to almost any two-dimensional table which contains non-negative values. For example, input data tables can contain作者: 濃縮 時間: 2025-3-29 10:11
Regularity and the number of clusters, curves introduced in Chapter 6. It will be shown that members of a parametrized family of two-dimensional distributions from the Bivariate Lilliputian Model (???)which are based on parabolas are ideally regular data tables (Sections 11.2–11.3).作者: 綁架 時間: 2025-3-29 12:35
Inequality measures for multivariate distributions,variate datasets with . sets of records. These measures are easy to percept for those who are familiar with the concepts of the Lorenz Curve and Gini Index which are so important in the univariate case.作者: FIS 時間: 2025-3-29 15:55
https://doi.org/10.1007/978-94-009-5145-7s, data were ordered according to increasing earnings. For earnings aggregated to four macrocategories, the concentration curve .(. : .) relating male earnings . to female earnings . happened to be convex. This indicated a clear monotone trend: the higher the earnings macrocategory, the stronger the作者: BARK 時間: 2025-3-29 20:13
https://doi.org/10.1007/978-1-4684-5203-7ack sufficient precision. It is due to the fact that there are many curves which have the same index value. Problems related to how greatly such curves may differ are discussed in Sec. 5.2. In particular, the boundaries of the smallest region containing all maximal concentration curves with a common作者: Ingest 時間: 2025-3-30 03:17 作者: Nausea 時間: 2025-3-30 04:43 作者: harpsichord 時間: 2025-3-30 09:17
C. Cheniclet,C. Bernard-Dagan,G. Paulyuced in Section 9.2. The basic procedure of GCA solves the problem of permuting the rows and columns of a probability table in order to maximize the value of the grade correlation .*. This is done by alternately permuting the rows and columns according to the respective grade regression function unt作者: olfction 時間: 2025-3-30 14:59
The Functional Role of Myocilin in Glaucomaescribed in Chapter 6 for pairs of random variables. Although the theoretical background assumes that the data must have the form of two-way probability tables, the method is applicable to almost any two-dimensional table which contains non-negative values. For example, input data tables can contain作者: temperate 時間: 2025-3-30 19:07
