Results 11 to 20 of about 305,718 (72)

Analyzing Quality Measurements for Dimensionality Reduction

Machine Learning and Knowledge Extraction, 2023
Dimensionality reduction methods can be used to project high-dimensional data into low-dimensional space. If the output space is restricted to two dimensions, the result is a scatter plot whose goal is to present insightful visualizations of distance ...
Michael C. Thrun, Julian Märte, Quirin Stier   +2 more
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Dimensionality Reduction for Handwritten Digit Recognition [PDF]

EAI Endorsed Transactions on Cloud Systems, 2018
Human perception of dimensions is usually limited to two or three degrees. Any further increase in the number of dimensions usually leads to the difficulty in visual imagination for any person.
Ankita Das, Tuhin Kundu, Chandran Saravanan   +2 more
doaj   +1 more source

An Orthogonal Locality and Globality Dimensionality Reduction Method Based on Twin Eigen Decomposition

IEEE Access, 2021
Dimensionality reduction is a hot research topic in pattern recognition. Traditional dimensionality reduction methods can be separated into linear dimensionality reduction methods and nonlinear dimensionality reduction methods.
Shuzhi Su, Gang Zhu, Yanmin Zhu
doaj   +1 more source

Adaptive slope reliability analysis method based on sliced inverse regression dimensionality reduction

Frontiers in Ecology and Evolution, 2023
The response surface model has been widely used in slope reliability analysis owing to its efficiency. However, this method still has certain limitations, especially the curse of high dimensionality when considering the spatial variability of ...
Zheng Zhou, Zheng Zhou, Zheng Zhou, Hai-Bin Xiong, Hai-Bin Xiong, Hai-Bin Xiong, Wen-Xia Wu, Wen-Xia Wu, Yi-Jian Yang, Yi-Jian Yang, Yi-Jian Yang, Xu-Hai Yang, Xu-Hai Yang   +12 more
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Effective and efficient approach in IoT Botnet detection

Jurnal Ilmiah SINERGI, 2023
Internet of Things (IoT) technology presents an advantage to daily life, but this advantage is not a guarantee of security. This is because cyber-attacks, such as botnets, remain a threat to the user.
Susanto Susanto, Deris Stiawan, M. Agus Syamsul Arifin, Mohd. Yazid Idris, Rahmat Budiarto   +4 more
doaj   +1 more source

Uniform Manifold Approximation and Projection (UMAP) Reveals Composite Patterns and Resolves Visualization Artifacts in Microbiome Data

mSystems, 2021
Microbiome data are sparse and high dimensional, so effective visualization of these data requires dimensionality reduction. To date, the most commonly used method for dimensionality reduction in the microbiome is calculation of between-sample microbial ...
George Armstrong, Cameron Martino, Gibraan Rahman, Antonio Gonzalez, Yoshiki Vázquez-Baeza, Gal Mishne, Rob Knight   +6 more
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Dimensionality reduction by LPP‐L21

IET Computer Vision, 2018
Locality preserving projection (LPP) is one of the most representative linear manifold learning methods and well exploits intrinsic structure of data. However, the performance of LPP remarkably degenerate in the presence of outliers.
Shujian Wang, Deyan Xie, Fang Chen, Quanxue Gao   +3 more
doaj   +1 more source

Note About Null Dimensional Reduction of M5-Brane [PDF]

arXiv, 2021
In this short note we study null dimensional reduction of M5-brane covariant action. We analyse longitudinal dimensional reduction that leads to non-relativistic D4-brane and transverse reduction that leads to NS5-brane in non-relativistic string theory.
arxiv  

Using Dimensional Reduction for Hadronic Collisions [PDF]

Nucl.Phys.B808:88-120,2009, 2008
We discuss how to apply regularization by dimensional reduction for computing hadronic cross sections at next-to-leading order. We analyze the infrared singularity structure, demonstrate that there are no problems with factorization, and show how to use dimensional reduction in conjunction with standard parton distribution functions.
arxiv   +1 more source

Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis

Genome Biology, 2019
Background Dimensionality reduction is an indispensable analytic component for many areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality reduction can allow for effective noise removal and facilitate many downstream ...
Shiquan Sun, Jiaqiang Zhu, Ying Ma, Xiang Zhou   +3 more
doaj   +1 more source