Results 51 to 60 of about 141,001 (306)
Classification, dimensionality reduction, and maximally discriminatory visualization of a multicentre 1H-MRS database of brain tumors [PDF]
, 2008 The combination of an Artificial Neural Network classifier, a feature selection process, and a novel linear dimensionality reduction technique that provides a data projection for visualization and which preserves completely the class discrimination ...
Arús, Carles +9 more
core +1 more source
Regional-scale groundwater analysis with dimensionality reduction [PDF]
Natural Hazards and Earth System SciencesGiven the importance of groundwater for freshwater provision and groundwater-dependent ecosystems, understanding climate effects on groundwater changes at a regional scale is essential.
M. Somogyvári +9 more
doaj +1 more source
Dimensionality reduction in data from LASER applications [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2012 Redundant variables not only in LASER applications, but in all experimental works are disturbing statistical analysis as a result of highly correlation among them.
Imad H.Aboud, Qassim M. Jameel
doaj +1 more source
Non-negative Dimensionality Reduction for Mammogram Classification [PDF]
Journal of Electrical and Electronics Engineering, 2009 Directly classifying high dimensional datamay exhibit the ``curse of dimensionality'' issue thatwould negatively influence the classificationperformance with an increase in the computationalload, depending also on the classifier structure.
I. Buciu, A. Gacsadi
doaj
Dimensionality Reduction by Similarity Distance-Based Hypergraph Embedding
Atmosphere, 2022 Dimensionality reduction (DR) is an essential pre-processing step for hyperspectral image processing and analysis. However, the complex relationship among several sample clusters, which reveals more intrinsic information about samples but cannot be ...
Xingchen Shen, Shixu Fang, Wenwen Qiang
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Limitations on quantum dimensionality reduction [PDF]
International Journal of Quantum Information, 2011 The Johnson–Lindenstrauss Lemma is a classic result which implies that any set of n real vectors can be compressed to O( log n) dimensions while only distorting pairwise Euclidean distances by a constant factor. Here we consider potential extensions of this result to the compression of quantum states. We show that, by contrast with the classical case,
Aram W. Harrow +2 more
openaire +4 more sources
Quantum resonant dimensionality reduction
Physical Review ResearchQuantum computing is a promising candidate for accelerating machine learning tasks. Limited by the control accuracy of current quantum hardware, reducing the consumption of quantum resources is the key to achieving quantum advantage.
Fan Yang +6 more
doaj +1 more source
Linear Dimensionality Reduction: What Is Better?
DataThis research paper focuses on dimensionality reduction, which is a major subproblem in any data processing operation. Dimensionality reduction based on principal components is the most used methodology. Our paper examines three heuristics, namely Kaiser’
Mohit Baliyan, Evgeny M. Mirkes
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Adolescents with haematological malignancies face significant emotional and relational challenges, often accompanied by difficulties in communicating their needs within the healthcare context. To address these issues, a narrative‐based psycho‐educational intervention based on the creation and prescription of Ironic Medications was ...
Marta Stoppa +7 more
wiley +1 more source
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 Procrustes rotation and show that it leads to a better reconstruction of images.
Peña, Daniel, Benito, Mónica
openaire +3 more sources