Optimizing Euclidean Distance Computation

This paper presents a comparative analysis of seventeen different approaches to optimizing Euclidean distance computations, which is a core mathematical operation that plays a critical role in a wide range of algorithms, particularly in machine learning and data analysis. The Euclidean distance, bei...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Mathematics (Basel) Ročník 12; číslo 23; s. 3787
Hlavný autor:	Mussabayev, Rustam
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.12.2024
Predmet:	Algorithms Bioinformatics Clustering Comparative analysis Computational linguistics computational optimization Data analysis Data mining Data structures Datasets Efficiency Energy conservation Energy consumption Euclidean distance Euclidean geometry Euclidean space Geospatial data Germany Information management K-means clustering K-nearest neighbors (KNNs) Language processing Linear algebra Machine learning Mathematical optimization Methods Natural language interfaces Optimization parallelization Spatial data Task complexity vectorization Germany
ISSN:	2227-7390, 2227-7390
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!