Search results for "model performance"

showing 2 items of 2 documents

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

2020

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and &ldquo

Malenormal distributionobesity020205 medical informaticsNice02 engineering and technologyOverweightlcsh:Chemical technologycomputer.software_genreSklearnBiochemistryAnalytical ChemistryMachine Learning0302 clinical medicinePregnancyRisk Factors0202 electrical engineering electronic engineering information engineeringMedicinedata visualizationlcsh:TP1-1185030212 general & internal medicineInstrumentationVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550computer.programming_languageBehavior changeMiddle AgedAtomic and Molecular Physics and Opticssensor dataPeer reviewlifestyle diseasesVDP::Medisinske Fag: 700::Helsefag: 800classificationFemaleregressionmedicine.symptomAdultMachine learningArticle03 medical and health sciencesYoung AdultBMIUrbanizationHumansoverweightElectrical and Electronic EngineeringExercisegradient descentSedentary lifestylebusiness.industryWeight changemodel performancedeep learningeCoachmedicine.diseasecalibrationObesityhypothesis testpythonmonitoringArtificial intelligencePrismabusinesscomputerdiscriminationSensors (Basel, Switzerland)
researchProduct

Modéliser la réponse des espèces marines antarctiques aux changements environnementaux. Méthodes, applications et limites.

2021

Among tools that are used to fill knowledge gaps on natural systems, ecological modelling has been widely applied during the last two decades. Ecological models are simple representations of a complex reality. They allow to highlight environmental drivers of species ecological niche and better understand species responses to environmental changes. However, applying models to Southern Ocean benthic organisms raises several methodological challenges. Species presence datasets are often aggregated in time and space nearby research stations or along main sailing routes. Data are often limited in number to correctly describe species occupied space and physiology. Finally, environmental datasets …

[SDV.EE]Life Sciences [q-bio]/Ecology environmentphysiological modelModélisation écologiqueEspèces marines benthiquesmodel performancePhysiological modelsspecies distribution modellingModèles de distribution d’espècesOcéan Australdispersal model[SDV.EE] Life Sciences [q-bio]/Ecology environmentModèles de dispersion lagrangiensSpecies distribution modelsecological modellingLagrangian dispersal modelsSouthern OceanModèles physiologiquesEcological modellingMarine benthic speciesSciences exactes et naturelles
researchProduct