Results 11 to 20 of about 375,641 (168)
2D Dimensionality Reduction Methods without Loss [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application.
S. Ahmadkhani, P. Adibi, A. ahmadkhani
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Dimensionality Reduction Mappings [PDF]
, 2011 A wealth of powerful dimensionality reduction methods has been established which can be used for data visualization and preprocessing. These are accompanied by formal evaluation schemes, which allow a quantitative evaluation along general principles and ...
Biehl, Michael +3 more
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Supervised dimensionality reduction for big data
Nature Communications, 2021 Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for ...
Joshua T. Vogelstein +6 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 +4 more
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Haisu: Hierarchically supervised nonlinear dimensionality reduction.
PLoS Computational Biology, 2022 We propose a novel strategy for incorporating hierarchical supervised label information into nonlinear dimensionality reduction techniques. Specifically, we extend t-SNE, UMAP, and PHATE to include known or predicted class labels and demonstrate the ...
Kevin Christopher VanHorn +1 more
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Dimensionality reduction with image data [PDF]
, 2004 A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We propose a new method based on the projection of the images as matrices after a
Benito Bonito, Mónica +1 more
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Dimensionality reduction of clustered data sets [PDF]
, 2008 We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution of the model is an unsupervised generalisation of linear discriminant ...
Sanguinetti, G.
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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 +3 more
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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 +6 more
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Research on Dimensionality Reduction in Network Traffic Anomaly Detection [PDF]
Jisuanji gongcheng, 2020 To implement anomaly detection for a high dimensional network with mass flow data,data dimensionality should be reduced to relieve transmission and storage burdens from the system.This paper introduces network traffic anomaly detection process and ...
CHEN Liangchen, GAO Shu, LIU Baoxu, TAO Mingfeng
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