標(biāo)題: Titlebook: Data Analysis; Scientific Modeling Wolfgang Gaul,Otto Opitz,Martin Schader Book 2000 Springer-Verlag Berlin · Heidelberg 2000 Optimization [打印本頁(yè)] 作者: ALLY 時(shí)間: 2025-3-21 16:44
書目名稱Data Analysis影響因子(影響力)
書目名稱Data Analysis影響因子(影響力)學(xué)科排名
書目名稱Data Analysis網(wǎng)絡(luò)公開度
書目名稱Data Analysis網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Analysis被引頻次
書目名稱Data Analysis被引頻次學(xué)科排名
書目名稱Data Analysis年度引用
書目名稱Data Analysis年度引用學(xué)科排名
書目名稱Data Analysis讀者反饋
書目名稱Data Analysis讀者反饋學(xué)科排名
作者: 不理會(huì) 時(shí)間: 2025-3-21 23:33
Unobserved Heterogeneity in Mean- and Covariance Structure Modelshe likelihood function, estimation of the mixture model with regressors using three different EM algorithms, estimation of the asymptotic covariance matrix of parameters and testing for the number of mixture components. Finally, a small simulation study demonstrates good results for the two-stage EM algorithm in retrieving the original parameters.作者: Ingratiate 時(shí)間: 2025-3-22 00:31 作者: 本能 時(shí)間: 2025-3-22 05:27
Book 2000c modeling to practical application. They have devoted their latest contributions to a book edited to honor a colleague and friend, Hans-Hermann Bock, who has been active in this field for nearly thirty years.作者: Neuralgia 時(shí)間: 2025-3-22 09:05
1431-8814 scientific modeling to practical application. They have devoted their latest contributions to a book edited to honor a colleague and friend, Hans-Hermann Bock, who has been active in this field for nearly thirty years.978-3-540-67731-4978-3-642-58250-9Series ISSN 1431-8814 Series E-ISSN 2198-3321 作者: PRO 時(shí)間: 2025-3-22 13:30
1431-8814 mation age. It covers new areas with such trendy labels as, e.g., data mining or web mining as well as traditional directions emphazising, e.g., classification or knowledge organization. Leading researchers in data analysis have contributed to this volume and delivered papers on aspects ranging from作者: PRO 時(shí)間: 2025-3-22 18:02 作者: Provenance 時(shí)間: 2025-3-23 01:04
Erik J. Geiger,Nicholas M. Bernthal and Janowitz k-point inequality. The NP-hardness of finding a consensus dissimilarity for a pyramid (also called an indexed pseudo-hierarchy) is also proved in the case of one of the two possible alternatives for generalized average consensus.作者: pineal-gland 時(shí)間: 2025-3-23 02:32
Muhammad Omar Hakim,Andrew Eric Rosenbergequired or permitted. A variety of benefits are noted. In particular, this framework helps to establish the state-of-the-art and, thereby, guides future research. Potentially, all of this information can be made accessible as an interactive, updateable knowledge base.作者: 凹槽 時(shí)間: 2025-3-23 06:25 作者: Etching 時(shí)間: 2025-3-23 10:01 作者: condone 時(shí)間: 2025-3-23 14:52
Evidence for a Relationship Between Algorithmic Scheme and Shape of Inferred Treesference for sparse and chain-like trees. This phenomenon is explained by the difference between the a priori probability distributions induced by each scheme. An illustration is provided with the Mitochondrial Eve data set (Vigilant et al. 1991), and the practical impacts are discussed.作者: menopause 時(shí)間: 2025-3-23 19:29
Book 2000. It covers new areas with such trendy labels as, e.g., data mining or web mining as well as traditional directions emphazising, e.g., classification or knowledge organization. Leading researchers in data analysis have contributed to this volume and delivered papers on aspects ranging from scientifi作者: Prostaglandins 時(shí)間: 2025-3-23 23:38 作者: 打包 時(shí)間: 2025-3-24 05:41
Average Consensus in Numerical Taxonomy and Some Generalizations and Janowitz k-point inequality. The NP-hardness of finding a consensus dissimilarity for a pyramid (also called an indexed pseudo-hierarchy) is also proved in the case of one of the two possible alternatives for generalized average consensus.作者: 大溝 時(shí)間: 2025-3-24 06:37
On a Framework for Dissimilarity Analysisequired or permitted. A variety of benefits are noted. In particular, this framework helps to establish the state-of-the-art and, thereby, guides future research. Potentially, all of this information can be made accessible as an interactive, updateable knowledge base.作者: BAN 時(shí)間: 2025-3-24 13:04
Projections Distinguishing Isolated Groups in Multivariate Data Spacesch such groups are distinguished best. These procedures involve maximization of either a sum of correlation ratios, or a sum of between-groups variances. It is shown that the use of correlation ratios often leads to trivial dimensions corresponding to directions in the configuration along which the data hardly vary.作者: CODA 時(shí)間: 2025-3-24 17:21
Nucleus Basalis Lesions and Recoveryonstrained distance matrices with at most two off-main diagonal positive entries. Several bijections between non-hierarchical clustering structures and order-constrained distance matrices are established.作者: 配置 時(shí)間: 2025-3-24 20:18
Radiation Therapy for Chondrosarcomahe likelihood function, estimation of the mixture model with regressors using three different EM algorithms, estimation of the asymptotic covariance matrix of parameters and testing for the number of mixture components. Finally, a small simulation study demonstrates good results for the two-stage EM algorithm in retrieving the original parameters.作者: 一瞥 時(shí)間: 2025-3-25 00:35 作者: 妨礙 時(shí)間: 2025-3-25 06:33
Clustering Relational Dataks) problems are essentially special cases of the clustering relational data problem. An overview of the main results in this field, some open problems and directions for the future research are presented.作者: 古代 時(shí)間: 2025-3-25 08:46
Automatic Classification with Classifying Automata given input word belongs to the language recognized by this automaton. In the following, we will present an extended automata model, which we developed to construct and efficiently handle representations of dialog-controlled rule systems and to discover inconsistencies within their knowledge bases.作者: 哭得清醒了 時(shí)間: 2025-3-25 15:26 作者: 遷移 時(shí)間: 2025-3-25 16:04 作者: 咆哮 時(shí)間: 2025-3-25 20:50 作者: Abominate 時(shí)間: 2025-3-26 04:09 作者: deceive 時(shí)間: 2025-3-26 06:44 作者: 溝通 時(shí)間: 2025-3-26 11:30
On a Framework for Dissimilarity Analysiss are the class of representations concerned, the criterion function employed, and the transformations of data and/or representation that are either required or permitted. A variety of benefits are noted. In particular, this framework helps to establish the state-of-the-art and, thereby, guides futu作者: cocoon 時(shí)間: 2025-3-26 15:53
Least-Squares Ultrametric Tree Representations of Three- Way One-Mode Proximity Dataarity data. The three-way distance among any three terminal nodes of an ultrametric tree is defined as the weight attached to the lowest common ancestor of the three nodes. A mathematical programming procedure is described for finding an ultrametric tree whose three-way distances approximate the cor作者: 沙草紙 時(shí)間: 2025-3-26 19:06 作者: Outmoded 時(shí)間: 2025-3-27 00:40
Testing for Antimodes.., and a distribution . ∈ ..,the set of uniform mixtures with at most . modes. The . — 1 antimodes obtained in the best fitting .—modal distributions, collected for all .,form a hierarchical tree of intervals. To decide which of these empirical antimodes corresponds to an antimode in the true distr作者: 謙卑 時(shí)間: 2025-3-27 03:39 作者: Optimum 時(shí)間: 2025-3-27 07:33
Robust Forecasting of Parametric Trend of Time Series under “Outliers”tion algorithms with traditional least squares estimators and robust Huber estimators of parameters are obtained. The robust to “outliers” local-median prediction algorithm is presented. Results of computer modelling of prediction algorithms are given and analyzed.作者: gruelling 時(shí)間: 2025-3-27 11:08
Projections Distinguishing Isolated Groups in Multivariate Data Spacesata space. Four procedures are proposed for finding projections of the high-dimensional data configuration onto a small number of dimensions along which such groups are distinguished best. These procedures involve maximization of either a sum of correlation ratios, or a sum of between-groups varianc作者: OVER 時(shí)間: 2025-3-27 14:47 作者: 脫離 時(shí)間: 2025-3-27 21:31
Testing for Antimodesom a monotone density fit in the shoulder interval, and the reference distribution for it is the maximum empirical excursion for a sample from the uniform with the same sample size as the number of points in the shoulder interval. We demonstrate that this reference distribution gives approximately v作者: Jargon 時(shí)間: 2025-3-27 22:33
A Classification of Bivariate Negative Binomial Distributionsial distribution that is . multinomial is obtained from a randomly-stopped sums distribution: the product of a Poisson-logarithmic series distribution with only one marginal distribution being negative binomial, postmultiplied by the stochastic matrix of its transpose. Many other types of negative b作者: Concomitant 時(shí)間: 2025-3-28 05:33
Systemic Therapy for Chondrosarcomamixture of cubic B-splines in an interactive symbolic computational environment to obtain the maximum likelihood estimators of the parameters and to evaluate model selection criteria such as AIC (Akaike, 1973), CAIC (Bozdogan, 1987), and ICOMP (Bozdogan 1988,1990, 1993, 1994) in objectively detectin作者: 放氣 時(shí)間: 2025-3-28 09:51
https://doi.org/10.1057/9780230375758om a monotone density fit in the shoulder interval, and the reference distribution for it is the maximum empirical excursion for a sample from the uniform with the same sample size as the number of points in the shoulder interval. We demonstrate that this reference distribution gives approximately v作者: 明智的人 時(shí)間: 2025-3-28 12:35
https://doi.org/10.1057/9780230375758ial distribution that is . multinomial is obtained from a randomly-stopped sums distribution: the product of a Poisson-logarithmic series distribution with only one marginal distribution being negative binomial, postmultiplied by the stochastic matrix of its transpose. Many other types of negative b作者: 谷類 時(shí)間: 2025-3-28 16:16 作者: SOB 時(shí)間: 2025-3-28 20:41 作者: bacteria 時(shí)間: 2025-3-29 01:28 作者: concentrate 時(shí)間: 2025-3-29 03:40
Advances in Alzheimer Disease Therapyves an accurate estimation of the density probabity function of the data, an adapted hierarchical clustering allows to take into account an extra knowledge given by an expert. We present two actual applications of the method taken in the domain of geophysics.作者: 享樂主義者 時(shí)間: 2025-3-29 10:01
Radiation Therapy for Chondrosarcomamixtures of multivariate normals where the expected value for each component depends on possibly non-normal regressor variables. The expected values and covariance matrices of the mixture components are parameterized using conditional mean- and covariance-structures. We discuss the construction of t作者: Communal 時(shí)間: 2025-3-29 14:47
Erik J. Geiger,Nicholas M. Bernthalsensus dissimilarities out of a . of dissimilarities is NP-hard for ultrametrics, quasi-utrametrics and proper dissimilarities satisfying the Bertrand and Janowitz k-point inequality. The NP-hardness of finding a consensus dissimilarity for a pyramid (also called an indexed pseudo-hierarchy) is also作者: disrupt 時(shí)間: 2025-3-29 17:59
Systemic Therapy for Chondrosarcomaality of a given multivariate data set using an unsupervised mixture of cubic B-Spline in density estimation in one dimensional spece. In the multivariate case, this is achieved by utilizing the Mahalanobis (1936) distance of each point from the multivariate mean (centroid), Mahalanobis distance dat作者: Infant 時(shí)間: 2025-3-29 19:50
Muhammad Omar Hakim,Andrew Eric Rosenbergs are the class of representations concerned, the criterion function employed, and the transformations of data and/or representation that are either required or permitted. A variety of benefits are noted. In particular, this framework helps to establish the state-of-the-art and, thereby, guides futu作者: 侵蝕 時(shí)間: 2025-3-30 00:15 作者: aerobic 時(shí)間: 2025-3-30 06:21
https://doi.org/10.1057/9780230375758ively agglomerates pairs of leaves to form larger and larger clusters, while the latter proceeds by stepwise addition of objects to a growing tree. A third approach involves improving the global fitness of an initial tree by exchanging subtrees. This article suggests that the shape of inferred trees作者: idiopathic 時(shí)間: 2025-3-30 09:10
https://doi.org/10.1057/9780230375758.., and a distribution . ∈ ..,the set of uniform mixtures with at most . modes. The . — 1 antimodes obtained in the best fitting .—modal distributions, collected for all .,form a hierarchical tree of intervals. To decide which of these empirical antimodes corresponds to an antimode in the true distr作者: 委托 時(shí)間: 2025-3-30 14:16 作者: 任命 時(shí)間: 2025-3-30 16:43 作者: orthodox 時(shí)間: 2025-3-30 23:54 作者: 帳單 時(shí)間: 2025-3-31 02:00
https://doi.org/10.1007/978-3-642-58250-9Optimization Methods; Symbol; algorithms; calculus; classification; clustering; communication; data analysi作者: Estimable 時(shí)間: 2025-3-31 08:51 作者: foppish 時(shí)間: 2025-3-31 10:21
Anna N. Bukiya,Avia Rosenhouse-DantskerThe paper presents an iterative relocation algorithm that seeks to partition the descriptions of Boolean symbolic objects into classes so as to minimize the sum of the description potentials of the classes.作者: catagen 時(shí)間: 2025-3-31 15:26
Nucleus Basalis Lesions and RecoveryThe method of . has proved a powerful method for reducing the error rate in Bayesian pattern recognition. The method serves to recover from ambiguities often not avoidable during the early stage of processing. Applications of this method to object identification, supervised classification, and clustering are discussed.作者: 曲解 時(shí)間: 2025-3-31 18:37 作者: aspect 時(shí)間: 2025-4-1 00:35 作者: 合乎習(xí)俗 時(shí)間: 2025-4-1 05:13
Classification and Clustering of Objects With VariantsThe method of . has proved a powerful method for reducing the error rate in Bayesian pattern recognition. The method serves to recover from ambiguities often not avoidable during the early stage of processing. Applications of this method to object identification, supervised classification, and clustering are discussed.作者: 輕浮女 時(shí)間: 2025-4-1 07:53
From Data Mining to Knowledge Mining: An Introduction to Symbolic Data AnalysisThe need to extend standard data analysis methods (exploratory, clustering, factorial analysis, discrimination,…) to more complex data table is increasing in order to get more accurate information and summarize extensive data sets contained in huge databases. We define . (SDA) as the extension of standard Data Mining to such data tables.作者: 填滿 時(shí)間: 2025-4-1 13:05 作者: 絕種 時(shí)間: 2025-4-1 16:21
