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Titlebook: Advances in Principal Component Analysis; Research and Develop Ganesh R. Naik Book 2018 Springer Nature Singapore Pte Ltd. 2018 Principal C

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樓主
發(fā)表于 2025-3-21 17:39:53 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Principal Component Analysis
期刊簡稱Research and Develop
影響因子2023Ganesh R. Naik
視頻videohttp://file.papertrans.cn/150/149443/149443.mp4
發(fā)行地址Covers the latest, cutting-edge topics in PCA, with a focus on open problems.Balances theory and applications, with concrete examples.Offers in-depth analysis of PCA topics simply not covered anywhere
圖書封面Titlebook: Advances in Principal Component Analysis; Research and Develop Ganesh R. Naik Book 2018 Springer Nature Singapore Pte Ltd. 2018 Principal C
影響因子.This book reports on the latest advances in concepts and further developments of principal component analysis (PCA), addressing a number of open problems related to dimensional reduction techniques and their extensions in detail. Bringing together research results previously scattered throughout many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA.. . .
Pindex Book 2018
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發(fā)表于 2025-3-21 20:24:52 | 只看該作者
Principal Component Analysis in the Presence of Missing Data,e third quarter of the nineteenth century; and this remained largely true down to the end of the century and beyond, despite waves of unionisation among less skilled groups. The unionised minority was concentrated, as one might expect, among skilled men or others with a measure of job control which
板凳
發(fā)表于 2025-3-22 01:01:16 | 只看該作者
Outlier-Resistant Data Processing with L1-Norm Principal Component Analysis,e for the natural inclination always to regard one’s own age as a time of crisis, it also seems almost certainly a crucial phase. Four revolutionary developments, completely changing the whole character ofworld affairs, have made themselves apparent since the end of the recent war; the reason why th
地板
發(fā)表于 2025-3-22 06:08:59 | 只看該作者
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發(fā)表于 2025-3-22 09:24:12 | 只看該作者
Principal Component Analysis for Exponential Family Data,f our young days who were not literary at all — I remember getting into trouble for calling them electioneering rhymers.’. In complete contrast to his emphasis only a few years earlier on the need to create an ‘a(chǎn)ristocratic, esoteric Irish literature’, his plan for improving these contemporary poets
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發(fā)表于 2025-3-22 13:32:07 | 只看該作者
Principal Component Analysis in the Presence of Missing Data,e abysmal poverty of most workers. Destruction of union organisation by systematic victimisation and lock-out, leaving many firms ‘closed’ to unionists for years afterwards, could easily occur even in the best-organised trades; such experiences were central to the class consciousness of skilled labour.
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發(fā)表于 2025-3-22 20:03:18 | 只看該作者
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發(fā)表于 2025-3-22 22:41:36 | 只看該作者
Principal Component Analysis for Exponential Family Data,ition, but when he began writing political ballads he used the concreteness and rhetorical energy he had learned from dialect syntax to invoke that other, very different tradition of Young Ireland ‘electioneering’ verse which in 1895 he had rejected as spurious.
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發(fā)表于 2025-3-23 02:16:40 | 只看該作者
https://doi.org/10.1007/978-1-4613-3129-2duction using kernel PCA (one of the non linear PCA) and its modification i.e., clustering oriented kernel PCA in this field are elaborated in this chapter. Advantages and disadvantages of all these methods are experimentally evaluated over few hyperspectral data sets with different performance meas
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發(fā)表于 2025-3-23 08:29:49 | 只看該作者
https://doi.org/10.1007/978-1-4684-2706-6e of volumes. Results indicate that, in both cases, PCA can be used for effective compression with minimal loss of perceptual quality, and could benefit applications such as client-server visualization systems.
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