Results 121 to 130 of about 88,237 (314)
yaImpute: An R Package for kNN Imputation
This article introduces yaImpute, an R package for nearest neighbor search and imputation. Although nearest neighbor imputation is used in a host of disciplines, the methods implemented in the yaImpute package are tailored to imputation-based forest ...
Andrew O. Finley, Nicholas L. Crookston
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The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry
Agribusiness, EarlyView.ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source
Forecasting Italian electricity market prices with the nearest neighbors methods
openIn questo lavoro è stato sviluppato e testato un approccio di previsione dei prezzi orari del mercato elettrico italiano basato sul metodo dei vicini più vicini (kNN).
RUSSO, FEDERICO
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Magneto-electric effect of KNN-Ni composites [PDF]
, 2011 Conference Name:2011 International Symposium on Advanced Packaging Materials, APM 2011. Conference Address: Xiamen, China. Time:October 25, 2011 - October 28, 2011.A conversion was facilitated with magneto-electric effect between energies stored in ...
Xiong, Zhaoxian +9 more
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Automatic Determination of Quasicrystalline Patterns from Microscopy Images
Advanced Intelligent Discovery, EarlyView.This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender +2 more
wiley +1 more source
Context-Aware Job Recommender System
JOIV: International Journal on Informatics VisualizationContext-aware recommendation systems have emerged as essential to interactive web content and online job search. Primarily, since so many job offers are published on different online platforms, it can make the users take some time to find good ...
Muhammad Haziq Fikri Bin Azri +3 more
doaj +1 more source
Comparison between KNN, W-KNN, Wc-KNN and Wk-KNN models on a CDC heart disease dataset
Abstract One of the most popular and fundamental methods used for machine learning classification is KNN (K-nearest neighbor). Despite its simplicity, this method can achieve good data classification results even without prior knowledge of the data distribution.
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia +3 more
wiley +1 more source
Prediction of Telkomsel 4G LTE Card Sales using The K-Nearest Neighbor Algorithm
Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan KomputerAccurate sales prediction is a critical challenge in business decision-making, as factors such as data imbalance, outliers, and overfitting may compromise the reliability of predictive models.
Alfiana Fontes Martins +4 more
doaj +1 more source
Secure efficient federated KNN for recommendation systems
, 2020 K-nearest neighbors (KNN) has been successfully used for recommendation, but querying neighbors of high quality is nearly impossible when the feature space is small and has limited training data.
Liu, Zhaorong
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