Results 11 to 20 of about 3,487,202 (255)
Dimensionality Reduction by Weighted Connections between Neighborhoods [PDF]
Abstract and Applied Analysis, 2014 Dimensionality reduction is the transformation of high-dimensional data into a meaningful representation of reduced dimensionality. This paper introduces a dimensionality reduction technique by weighted connections between neighborhoods to improve K ...
Fuding Xie, Yutao Fan, Ming Zhou
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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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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 +2 more
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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
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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 +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 +4 more
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Dimensionality Reduction with Nvidia Tensor Cores [PDF]
, 2022 openThanks to the popularity and effectiveness of machine learning, the computational requirements for its development have increased beyond the limits of conventional devices.
BALZAN, PIETRO
core
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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New approaches on dimensionality reduction in hyperspectral images for classification purposes [PDF]
, 2012 This paper presents a quasi-unsupervised methodology to detect endmembers within an hyperspectral scene and to derive a pixel-wise classification on its basis.
Rupert Mueller +7 more
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Ten quick tips for effective dimensionality reduction.
PLoS Computational Biology, 2019 Ten quick tips for effective dimensionality ...
Lan Huong Nguyen, Susan Holmes
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