Agricultural Water ManagementClimate change and human activities have diminished the stability of the water resources system, leading to multiple uncertainties in the prediction of incoming water, reservoir operation optimization on the water supply side, and adaptive adjustments of
Zhan Shu +7 more
doaj +2 more sources
Revealing Brain Tumor Using Cross-Validated NGBoost Classifier
International Journal of Machine Learning and Networked Collaborative Engineering, 2020 Abstract Brain is the most complicated and delicate anatomical structure in human body. Statistics proves that, among various brain ailments, brain tumor is most fatal and in many cases they become carcinogenic. Brain tumor is characterized by abnormal and uncontrolled growth of brain cells, and takes up space within the cranial cavity and ...
Shawni Dutta +1 more
openaire +3 more sources
From Composition to Ionic Conductivity: Machine Learning-Guided Discovery and Experimental Validation of Argyrodite-Type Lithium-Ion Electrolytes. [PDF]
SmallA composition‐driven machine learning framework, Elements‐To‐Ionics (E2I), is developed to predict the ionic conductivity of argyrodite‐type Li6PS5I solely from elemental features. Guided by E2I, the targeted synthesis of multi‐element substitutions yielded high‐conductivity (>10−2 S cm−1) sulfide solid electrolytes after hot‐pressing.
Kong S +11 more
europepmc +2 more sources
Probabilistic prediction of oceanographic velocities with multivariate gaussian natural gradient boosting [PDF]
, 2023 Many single-target regression problems require estimates of uncertainty along with the point predictions. Probabilistic regression algorithms are well-suited for these tasks.
Rick Lumpkin +7 more
core +1 more source
A Hybridized NGBoost-XGBoost Framework for Robust Evaporation and Evapotranspiration Prediction [PDF]
, 2020 Abstract. We analyze the relationship between potential evapotranspiration (ETo), actual evapotranspiration (ETa), and surface water evaporation (Esw) in the semi-arid south-central Texas, using hourly climate data, daily lake evaporation measurements, and daily actual evapotranspiration measurements from an eddy covariance (EC) tower.
Başağaoğlu, Hakan +2 more
openaire +2 more sources
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
CoRR, 2019 We present Natural Gradient Boosting (NGBoost), an algorithm for generic probabilistic prediction via gradient boosting. Typical regression models return a point estimate, conditional on covariates, but probabilistic regression models output a full probability distribution over the outcome space, conditional on the covariates.
Tony Duan +6 more
openaire +3 more sources
Exploring Key Genes of Glutathione Metabolism in Systemic Lupus Erythematosus Based on Mendelian Randomisation, Single-Cell RNA Sequencing and Multiple Machine Learning Approaches. [PDF]
IET Syst BiolThis study identifies key metabolites and genes associated with systemic lupus erythematosus (SLE) by integrating Mendelian randomisation, multi‐omics, machine learning, and SHAP. It reveals the critical involvement of the glutathione metabolic pathway and highlights LAP3 as a key gene in SLE development.
Wang K, Li X, Tang Y, Zhao L.
europepmc +2 more sources
, 2021 International audienceThis study was aimed at investigating the determinants of environmental sustainability in 86 countries from 2007 to 2018. The natural gradient boosting (NGBoost) algorithm was implemented along with five machine learning models to ...
Jabeur, Sami Ben +7 more
core +1 more source
Relationship between Successive Flares in the Same Active Region and Space-Weather HMI Active Region Patch (SHARP) Parameters [PDF]
, 2022 A solar active region (AR) may produce multiple notable flares during its passage across the solar disk. We investigate successive flares from flare-eruptive active regions, and explore their relationship with solar magnetic parameters.
Guo, Yang +3 more
core +1 more source
Multivariate Probabilistic Regression with Natural Gradient Boosting
, 2021 Many single-target regression problems require estimates of uncertainty along with the point predictions. Probabilistic regression algorithms are well-suited for these tasks.
Sykulski, Adam +3 more
core +2 more sources