Results 11 to 20 of about 4,393,923 (290)
, 2021 When data objects that are the subject of analysis using machine learning techniques are described by a large number of features (i.e. the data is high dimension) it is often beneficial to reduce the dimension of the data. Dimension reduction can be beneficial not only for reasons of computational efficiency but also because it can improve the accuracy
Cunningham, Pádraig
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Some statistical methods for dimension reduction [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe aim of the work in this thesis is to carry out dimension reduction (DR) for high dimensional (HD) data by using statistical methods for variable ...
Al-Kenani, Ali J Kadhim
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Multi-Label Learning via Feature and Label Space Dimension Reduction
IEEE Access, 2020 In multi-label learning, each object belongs to multiple class labels simultaneously. In the data explosion age, the size of data is often huge, i.e., large number of instances, features and class labels.
Jun Huang +4 more
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Hyperspectral Image Classification via Information Theoretic Dimension Reduction
Remote Sensing, 2023 Hyperspectral images (HSIs) are one of the most successfully used tools for precisely and potentially detecting key ground surfaces, vegetation, and minerals.
Md Rashedul Islam +4 more
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CoRR, 2021 83 pages, 36 figures, to appear in the Cambridge University Press Elements in Quantitative and Computational Methods for the Social Sciences ...
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AN ADAPTIVE COMPOSITE QUANTILE APPROACH TO DIMENSION REDUCTION [PDF]
, 2014 Sufficient dimension reduction [Li 1991] has long been a prominent issue in multivariate nonparametric regression analysis. To uncover the central dimension reduction space, we propose in this paper an adaptive composite quantile approach.
Kong, Efang
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Evolutionary dimension reduction in phenotypic space
Physical Review Research, 2020 In general, cellular phenotypes, as measured by concentrations of cellular components, involve large number of degrees of freedom. However, recent measurement has demonstrated that phenotypic changes resulting from adaptation and evolution in response to
Takuya U. Sato, Kunihiko Kaneko
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kag85/RHEED-Dimension-Reduction: Journal of Applied Physics
, 2021 An explanation of how to use dimension reduction methods PCA, NMF, and kmeans, on RHEED ...
kag85
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Quantile treatment effect estimation with dimension reduction
Statistical Theory and Related Fields, 2020 Quantile treatment effects can be important causal estimands in evaluation of biomedical treatments or interventions for health outcomes such as medical cost and utilisation.
Ying Zhang +3 more
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Dimension reduction with expectation of conditional difference measure
Statistical Theory and Related Fields, 2023 In this article, we introduce a flexible model-free approach to sufficient dimension reduction analysis using the expectation of conditional difference measure.
Wenhui Sheng, Qingcong Yuan
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