TY  - JOUR
T1  - The Comparative Effects of Clustering Algorithms on CPU and GPU
AU  - Ersoy, Pınar
AU  - Erşahin, Mustafa
AU  - Erşahin, Buket
PY  - 2022
DA  - October
JF  - Artificial Intelligence Theory and Applications
JO  - AITA
PB  - İzmir Bakırçay Üniversitesi
WT  - DergiPark
SN  - 2757-9778
SP  - 19
EP  - 27
VL  - 2
IS  - 2
LA  - en
AB  - The algorithm clustering can be defined as the operation of separating the populace or pieces of information into various groups. This article aims to construct a performance comparison for Partitional Clustering by using random, k-means++ algorithms implemented with Scikit-Learn and k-means++, Tunnel k-means algorithms implemented with TensorFlow-GPU by means of their execution times. As a final output, a related comparison table will be printed by supplying their framework specifications. Since the article does not focus on the context of data, the necessary data sets will be produced in a random manner.
KW  - clustering
KW  - random k-means
KW  - k-means++
KW  - tunnel k-means
KW  - algorithm performance
KW  - TensorFlow-GPU
KW  - Scikit-Learn
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UR  - https://dergipark.org.tr/en/pub/aita/issue//1141500
L1  - https://dergipark.org.tr/en/download/article-file/2529257
ER  -