Principal Component Analysis (PCA) and feature importance-based dimension reduction for Reference Evapotranspiration (ET <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si169.svg" display="inline" id="d1e2315"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> </mml:math> ) predictions of Taif, Saudi Arabia
Rab Nawaz Bashir, Olfa Mzoughi, Muhammad Ali Shahid, Nazik Alturki, Oumaima Saidani
Topics & Concepts
Principal component analysisDimensionality reductionDimension (graph theory)Feature (linguistics)Reduction (mathematics)Scalable Vector GraphicsArtificial intelligenceMathematicsEvapotranspirationComponent (thermodynamics)Pattern recognition (psychology)Computer scienceAlgorithmArithmeticCombinatoricsGeometryPhysicsWorld Wide WebBiologyLinguisticsPhilosophyThermodynamicsEcologyPlant Water Relations and Carbon DynamicsHydrological Forecasting Using AIHydrology and Drought Analysis