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Theoretical characterization of uncertainty in high-dimensional linear classification
Machine Learning: Science and Technology, 2023 Being able to reliably assess not only the accuracy but also the uncertainty of models’ predictions is an important endeavor in modern machine learning. Even if the model generating the data and labels is known, computing the intrinsic uncertainty after ...
Lucas Clarté +3 more
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Agricultural and Food Economics, 2020 The debate about the contribution of urban agriculture to urban household food security has not considered the possible differential effects by geography of production activities, focusing either on urban household’s participation in agriculture ...
Hayford Mensah Ayerakwa +2 more
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BMJ OpenObjective To study the progression of newly diagnosed breast cancer patients towards cardioembolic disorders (CDs) and ischaemic or structural heart disease (ISH) within a multistate framework that includes death as an absorbing state, in order to ...
Marianne Klemp, Ingunn Fride Tvete
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The extension of the largest generalized-eigenvalue based distance metric ) in arbitrary feature spaces to classify composite data points [PDF]
Genomics & Informatics, 2019 Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate ...
Mosaab Daoud
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Automatic Detection of Cognitive Impairment with Virtual Reality
Sensors, 2023 Cognitive impairment features in neuropsychiatric conditions and when undiagnosed can have a severe impact on the affected individual’s safety and ability to perform daily tasks.
Farzana A. Mannan +4 more
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The Astrophysical Journal Supplement SeriesThe dipole anisotropy in galaxy and QSO number counts induced by the observer’s motion, known as the kinematic dipole, provides an important test of cosmological isotropy and an independent comparison with the dipole of the cosmic microwave background ...
Tsutomu T. Takeuchi
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Stacking Ensemble Learning for Genomic Prediction Under Complex Genetic Architectures
AgronomyGenomic selection (GS) estimates the GEBV from genome-wide markers to reduce generation intervals and optimize germplasm selection, which is particularly advantageous for high-cost or late-expressed traits.
Maurício de Oliveira Celeri +6 more
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Impact of environmental covariates summarization on predictive ability in genomic selection
The Plant GenomeIntegrating genomic and environmental information holds the potential for enhancing the predictive power of genomic prediction models when accounting for the genotype‐by‐environment interactions.
Vitor Seiti Sagae +4 more
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Endoscopy International Open, 2018 Background and study aims The aim of this study was to develop a machine learning-based model to classify bowel cleansing quality and to test this model in comparison to a pixel analysis model and assessments by four colon capsule endoscopy (CCE) readers.
Maria Magdalena Buijs +6 more
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Image masks of global ship tracks for NASA MODIS data products
Scientific DataShip tracks, long thin artificial cloud features formed from the pollutants in ship exhaust, are satellite-observable examples of aerosol-cloud interactions (ACI) that can lead to increased cloud albedo and thus increased solar reflectivity, phenomena of
Pierce Warburton +3 more
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