چکیده مقاله
This paper has a review of the improved K Means clustering algorithms, which improve the shortcomings of the K Means algorithm and thus provide a better and more efficient algorithm for learning big data The goal is to cluster several large data sets, while maintaining the simplicity and efficiency of K Means All of these methods upgrade the standard K Means algorithm to an efficient algorithm for big data
کلیدواژهها
K-Means Clustering Big data Quality of Clustering Execution time initialization classification K Means Improvement of K Means algorithm
نویسندگان
Fatemeh Moodi
Ph D, Student, Yazd University, Yazd, Iran
Amir Jahangard-Rafsanjani
Assistant Professor Yazd University, Yazd, Iran
Sajjad Zarifzadeh
Associate Professor Yazd University, Yazd, Iran
Hamid Saadatfar
Assistant Professor, Birjand University, South Of Khorasan, Birjand, Iran
شیوه ارجاع
Moodi, Fatemeh and Jahangard-Rafsanjani, Amir and Zarifzadeh, Sajjad and Saadatfar, Hamid,1401,A review of the improved K-Means Clustering Algorithms for big data,7th International Conference on Science & Technology with sustainable development approach,Tehran
ارائهشده در
مجموعه مقالات هفتمین همایش بین المللی علوم و تکنولوژی با رویکرد توسعه پایدار25 اسفند 1401 · تهران