標(biāo)題: Titlebook: Unsupervised Feature Extraction Applied to Bioinformatics; A PCA Based and TD B Y-h. Taguchi Book 20201st edition Springer Nature Switzerla [打印本頁] 作者: sustained 時(shí)間: 2025-3-21 20:09
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics影響因子(影響力)
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics影響因子(影響力)學(xué)科排名
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics網(wǎng)絡(luò)公開度
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics被引頻次
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics被引頻次學(xué)科排名
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics年度引用
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics年度引用學(xué)科排名
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics讀者反饋
書目名稱Unsupervised Feature Extraction Applied to Bioinformatics讀者反饋學(xué)科排名
作者: 發(fā)出眩目光芒 時(shí)間: 2025-3-21 20:35
Applications of PCA Based Unsupervised FE to BioinformaticsPCA based unsupervised FE ranges from biomarker identification and identification of disease causing genes to in silico drug discovery. I try to mention studies where PCA based unsupervised FE is applied as many as possible, from the published papers by myself.作者: conformity 時(shí)間: 2025-3-22 03:56
2522-848X g data.Includes several applications to multi-view data anal.This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have the作者: 喪失 時(shí)間: 2025-3-22 08:27
Matrix Factorization matrices used to represent the original matrix by multiplication are small enough (i.e., lower rank), it can be considered to be reduction of degrees of freedom. Even if the matrix cannot be exactly represented as a product of two lower rank matrices, if it is possible for the product of matrices w作者: MELON 時(shí)間: 2025-3-22 09:18
Tensor Decompositionf matrices are considered. In contrast to the MF that is usually represented as a product of two matrices, TD has various forms. In contrast to the matrices that were extensively studied over long period, tensor has much shorter history of extensive investigations, especially from the application po作者: brachial-plexus 時(shí)間: 2025-3-22 14:26
PCA Based Unsupervised FEecially when the number of features attributed to individual samples is too huge to interpret. Mathematically, PCA is nothing but a linear projection of objects in high dimensional space onto low dimensional space. Alternatively, PC can be considered to be a tool that performs feature extraction (FE作者: 不怕任性 時(shí)間: 2025-3-22 19:49
TD Based Unsupervised FEledge, e.g., class labeling and period. In this chapter, I introduce TD based unsupervised FE as a natural extension of PCA based unsupervised FE towards tensors. In contrast to PCA that can deal with only one feature, TD can deal with multiple features, e.g., gene expression and miRNA expression si作者: GRUEL 時(shí)間: 2025-3-22 23:07 作者: 安心地散步 時(shí)間: 2025-3-23 04:47 作者: keloid 時(shí)間: 2025-3-23 07:47
Book 20201st editionervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra作者: 上腭 時(shí)間: 2025-3-23 10:25 作者: Servile 時(shí)間: 2025-3-23 14:54
Matrix Factorizationith smaller rank to approximate the original one, it can be considered to be a good approximation. Matrix factorization also has some relationship with geometrical representation. Generated matrices can be considered to be projection onto lower dimensional space.作者: Factorable 時(shí)間: 2025-3-23 18:36
Application of TD Based Unsupervised FE to Bioinformatics such situations. The first situation is that data itself should be formatted in tensor rather than matrix. The second situation is the integrated analysis of more than two matrices. In this chapter, we will demonstrate in which situation TD based unsupervised FE is better to be applied.作者: hauteur 時(shí)間: 2025-3-23 22:23 作者: GREEN 時(shí)間: 2025-3-24 03:10
Book 20201st editionir application to a wide range of topics.?.Allows readers to analyze data sets with small samples and many features;.Provides a fast algorithm, based upon linear algebra, to analyze big data;.Includes several applications to multi-view data analyses, with a focus on bioinformatics..作者: 無表情 時(shí)間: 2025-3-24 09:55 作者: AGGER 時(shí)間: 2025-3-24 10:53 作者: 烤架 時(shí)間: 2025-3-24 15:42 作者: vanquish 時(shí)間: 2025-3-24 20:25
uthor should persuade, and left the text to speak for itself. It has, indeed, stimulated a steady interest, to the point that Springer-Verlag has now commission978-0-387-97764-5978-1-4612-2892-9Series ISSN 1431-875X Series E-ISSN 2197-4136 作者: mucous-membrane 時(shí)間: 2025-3-24 23:40 作者: 急性 時(shí)間: 2025-3-25 05:47
working in probability, stochastic analysis and harmonic analysis on groups. It will also be of interest to mathematicians working in Lie theory and physicists, statisticians and engineers who are working on r978-3-319-37579-3978-3-319-07842-7Series ISSN 2199-3130 Series E-ISSN 2199-3149 作者: 鈍劍 時(shí)間: 2025-3-25 10:13
Y-h. Taguchiistributions. Some of the longer chapters in the previous editions have been divided into shorter chapters to allow for more flexible teaching..Probability with Statistical Applications, Third Edition. is inten978-3-030-93637-2978-3-030-93635-8作者: Stricture 時(shí)間: 2025-3-25 12:31
2522-848X samples and many features;.Provides a fast algorithm, based upon linear algebra, to analyze big data;.Includes several applications to multi-view data analyses, with a focus on bioinformatics..978-3-030-22458-5978-3-030-22456-1Series ISSN 2522-848X Series E-ISSN 2522-8498 作者: IST 時(shí)間: 2025-3-25 17:05
Y-h. Taguchi different schools have expressed all their best, without managing to gain the upper hand. The difference might be, that in the case of the foundations of mathematics the new attitude is something like skepticism about the whole foundational enterprise, while in the case of probability the new attitude is rather that of tolerance.作者: 思想靈活 時(shí)間: 2025-3-25 23:43 作者: intercede 時(shí)間: 2025-3-26 00:53 作者: famine 時(shí)間: 2025-3-26 06:36 作者: 陰郁 時(shí)間: 2025-3-26 09:19 作者: 帶來墨水 時(shí)間: 2025-3-26 13:26
Introduction to Linear AlgebraAlthough the content in this chapter should be taught in much earlier life stages, graduate or undergraduate levels, of most possible reader, because this book mainly deals with somewhat data science oriented matters, it might not be a bad idea to reintroduce fundamental concepts in a data science oriented manner.作者: 婚姻生活 時(shí)間: 2025-3-26 17:53 作者: Contend 時(shí)間: 2025-3-26 22:02
Unsupervised and Semi-Supervised Learninghttp://image.papertrans.cn/u/image/942523.jpg作者: exhibit 時(shí)間: 2025-3-27 02:41
https://doi.org/10.1007/978-3-030-22456-1Matrix factorization; Tensor decompositions; PCA based unsupervised FE; TD based unsupervised FE; PCA/TD作者: 愛得痛了 時(shí)間: 2025-3-27 07:05
978-3-030-22458-5Springer Nature Switzerland AG 2020作者: buoyant 時(shí)間: 2025-3-27 10:41 作者: Graves’-disease 時(shí)間: 2025-3-27 16:46
apt that measure-theoretic background to the special needs o.This 2nd edition textbook.?.offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians—a textbook for courses in probability for students in mathematical st作者: 責(zé)任 時(shí)間: 2025-3-27 19:24 作者: 臭名昭著 時(shí)間: 2025-3-27 23:12
Y-h. Taguchil Conference on Probability in Banach Spaces, held at Sandjberg, Denmark, August 16-21, 1993. A glance at the table of contents indicates the broad range of topics covered at this conference. What defines research in this field is not so much the topics considered but the generality of the ques- tio作者: 羞辱 時(shí)間: 2025-3-28 03:54 作者: ALB 時(shí)間: 2025-3-28 09:51
sis for a graduate course.Includes supplementary material: .Probability theory on compact Lie groups deals with the interaction between “chance” and “symmetry,” a beautiful area of mathematics of great interest in its own sake but which is now also finding increasing applications in statistics and e
