標(biāo)題: Titlebook: Chemometrics with R; Multivariate Data An Ron Wehrens Book 2020Latest edition Springer-Verlag GmbH Germany, part of Springer Nature 2020 Mu [打印本頁] 作者: McKinley 時(shí)間: 2025-3-21 16:51
書目名稱Chemometrics with R影響因子(影響力)
書目名稱Chemometrics with R影響因子(影響力)學(xué)科排名
書目名稱Chemometrics with R網(wǎng)絡(luò)公開度
書目名稱Chemometrics with R網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Chemometrics with R被引頻次
書目名稱Chemometrics with R被引頻次學(xué)科排名
書目名稱Chemometrics with R年度引用
書目名稱Chemometrics with R年度引用學(xué)科排名
書目名稱Chemometrics with R讀者反饋
書目名稱Chemometrics with R讀者反饋學(xué)科排名
作者: 多山 時(shí)間: 2025-3-21 21:53 作者: obstinate 時(shí)間: 2025-3-22 02:12
,Nützliches im Umgang mit SPSS,As we saw earlier in the visualizations provided by methods like PCA and SOM, it is often interesting to look for structure, or groupings, in the data. However, these methods do not explicitly define clusters; that is left to the pattern recognition capabilities of the scientist studying the plot.作者: Fsh238 時(shí)間: 2025-3-22 07:14
Konzeptgebundene SteuerungsverfahrenThe goal of classification, also known as supervised pattern recognition, is to provide a model that yields the optimal discrimination between several classes in terms of predictive performance.作者: hedonic 時(shí)間: 2025-3-22 09:06 作者: Communicate 時(shí)間: 2025-3-22 14:31 作者: Communicate 時(shí)間: 2025-3-22 17:40
Self-Organizing MapsIn PCA, the most outlying data points determine the direction of the PCs—these are the ones contributing most to the variance. This often results in score plots showing a large group of points close to the center.作者: evasive 時(shí)間: 2025-3-22 22:33 作者: insurgent 時(shí)間: 2025-3-23 03:54 作者: Ingenuity 時(shí)間: 2025-3-23 06:55 作者: 溫室 時(shí)間: 2025-3-23 13:10
Chemometrics with R978-3-662-62027-4Series ISSN 2197-5736 Series E-ISSN 2197-5744 作者: 詞匯記憶方法 時(shí)間: 2025-3-23 16:30
Von der Forschungsfrage zur Datenerhebung,ata. It has many uses, perhaps the most important of which is the possibility to provide simple two-dimensional plots of high-dimensional data. This way, one can easily assess the presence of grouping or outliers, and more generally obtain an idea of how samples and variables relate to each other.作者: Stagger 時(shí)間: 2025-3-23 18:40
Principal Component Analysisata. It has many uses, perhaps the most important of which is the possibility to provide simple two-dimensional plots of high-dimensional data. This way, one can easily assess the presence of grouping or outliers, and more generally obtain an idea of how samples and variables relate to each other.作者: WITH 時(shí)間: 2025-3-23 23:51
Von der Forschungsfrage zur Datenerhebung,ata. It has many uses, perhaps the most important of which is the possibility to provide simple two-dimensional plots of high-dimensional data. This way, one can easily assess the presence of grouping or outliers, and more generally obtain an idea of how samples and variables relate to each other.作者: Retrieval 時(shí)間: 2025-3-24 03:29
https://doi.org/10.1007/978-3-531-90366-8s “supervised” in the sense that we use a set of examples with known class labels, the training set, to build the model. In this chapter we will do something similar—now we are not predicting a discrete class property but rather a continuous variable. Put differently: given a set of independent real作者: 引起痛苦 時(shí)間: 2025-3-24 07:10
Konzeptgebundene Steuerungsverfahren able to make accurate predictions (the position of a planet in two weeks’ time) is—in some sense—a “correct” description of reality. In many applications in the natural sciences, unfortunately, validation is hard to do: chemical and biological processes often exhibit quite significant variation unr作者: congenial 時(shí)間: 2025-3-24 14:35
Normierte Organisationsentwicklungsverfahreniques, found in many textbooks and applicable in a wide range of fields. The topics in this chapter are more specific to the field of chemometrics, combining elements from the previous chapters. In particular, latent-variable approaches like PCA and PLS exhibit a wide range of applications (some peo作者: 讓步 時(shí)間: 2025-3-24 18:39
https://doi.org/10.1007/978-3-662-62027-4Multivariate statistics; Clustering; Principal Component Analysis; R software; Variable Selection; Linear作者: 躲債 時(shí)間: 2025-3-24 23:00 作者: 光亮 時(shí)間: 2025-3-25 00:32 作者: avenge 時(shí)間: 2025-3-25 06:56 作者: Bravura 時(shí)間: 2025-3-25 09:16 作者: beta-cells 時(shí)間: 2025-3-25 15:05
https://doi.org/10.1007/978-3-531-90366-8ables, or at least are so much larger in the dependent variables that errors in the independent variables can be ignored. Of course, we also would like to have an estimate of the expected error in predictions for future data.作者: chapel 時(shí)間: 2025-3-25 18:59
Multivariate Regressionables, or at least are so much larger in the dependent variables that errors in the independent variables can be ignored. Of course, we also would like to have an estimate of the expected error in predictions for future data.作者: 四指套 時(shí)間: 2025-3-25 20:40
2197-5736 cible.Provides the R codes discussed in the text.This book offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive description of the general data analysis paradigm, from exploratory analysis (principal component analysis, sel作者: Dissonance 時(shí)間: 2025-3-26 00:42
Book 2020Latest editionon of the general data analysis paradigm, from exploratory analysis (principal component analysis, self-organizing maps and clustering) to modeling (classification, regression) and validation (including variable selection). It also includes a special section discussing several more specific topics i作者: FIN 時(shí)間: 2025-3-26 05:13
Normierte Organisationsentwicklungsverfahrenple have criticized the field of chemometrics of being too preoccupied with latent-variable methods, and not without reason—on the other hand such tools are extremely handy in many different situations).作者: 證明無罪 時(shí)間: 2025-3-26 11:39
Chemometric Applicationsple have criticized the field of chemometrics of being too preoccupied with latent-variable methods, and not without reason—on the other hand such tools are extremely handy in many different situations).作者: 現(xiàn)存 時(shí)間: 2025-3-26 15:23 作者: 起草 時(shí)間: 2025-3-26 18:53
2197-5736 on features not only updates on many of the topics covered, but also several sections of new material (e.g., on handling missing values in PCA, multivariate process monitoring and batch correction)...?.978-3-662-62026-7978-3-662-62027-4Series ISSN 2197-5736 Series E-ISSN 2197-5744 作者: 退潮 時(shí)間: 2025-3-26 22:20
Konzeptgebundene Steuerungsverfahren consistent experimental design will be able to prevent this kind of fluctuations. Moreover, biological variation between individuals often dominates measurement variation. The bigger the variation, the more important it is to have enough samples for validation. Only in this way, reliable error esti作者: 分解 時(shí)間: 2025-3-27 04:46 作者: 桶去微染 時(shí)間: 2025-3-27 08:30 作者: 歪曲道理 時(shí)間: 2025-3-27 10:03
Validation able to make accurate predictions (the position of a planet in two weeks’ time) is—in some sense—a “correct” description of reality. In many applications in the natural sciences, unfortunately, validation is hard to do: chemical and biological processes often exhibit quite significant variation unr作者: BULLY 時(shí)間: 2025-3-27 13:53
Chemometric Applicationsiques, found in many textbooks and applicable in a wide range of fields. The topics in this chapter are more specific to the field of chemometrics, combining elements from the previous chapters. In particular, latent-variable approaches like PCA and PLS exhibit a wide range of applications (some peo作者: 書法 時(shí)間: 2025-3-27 20:00
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10樓
