Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data-Reference-Cited by-同舟云学术

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Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data

Published:2020-05 Issue:5 Volume:28 Page:874-886
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Maillo Jesus^ORCID,Garcia Salvador,Luengo Julian,Herrera Francisco^ORCID,Triguero Isaac^ORCID

Funder

Spanish National Research Project

Formación de Profesorado Universitario

Spanish Ministry of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/91/9084392/08807277.pdf?arnumber=8807277

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3. Enhancing gastric cancer early detection: A multi-verse optimized feature selection model with crossover-information feedback;Computers in Biology and Medicine;2024-06

4. Maternal Health Risk Classification - A Comparison between Algorithm Decision Tree and k-Nearest Neighbor (kNN);2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET);2023-09-14

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