TY  - JOUR 
AU  - Hassanat, Ahmad
PY  - 2018
SN  - 2255-2863
UR  - http://hdl.handle.net/10366/139224
AB  - Finding the diameter of a dataset in multidimensional Euclidean space is a well-established problem, with well-known algorithms. However, most of the algorithms found in the literature do not scale well with large values of data dimension, so the time...
LA  - eng
PB  - Ediciones Universidad de Salamanca (España)
KW  - Computación
KW  - Informótica
KW  - Computing
KW  - Information Technology
TI  - Greedy Algorithms for Approximating the Diameter of Machine Learning Datasets in Multidimensional Euclidean Space: Experimental Results
ER  -