Results 51 to 60 of about 30,970,765 (331)

K-means and fuzzy c-means algorithm comparison on regency/city grouping in Central Java Province

open access: yesDesimal, 2022
The Human Development Index (HDI) is very important in measuring the country's success as an effort to build the quality of life of people in a region, including Indonesia. The government needs to make groupings based on the needs of a city/district.
Ummu Wachidatul Latifah   +2 more
doaj   +1 more source

B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM

open access: yesJournal of Theoretical and Applied Electronic Commerce Research, 2022
Customer churn prediction is very important for e-commerce enterprises to formulate effective customer retention measures and implement successful marketing strategies.
Xiancheng Xiahou, Yoshio Harada
semanticscholar   +1 more source

The comparative study of text documents clustering algorithms

open access: yesEnvironment Conservation Journal, 2015
Clustering is one of the most significant research area in the field of data mining and considered as an important tool in the fast developing information explosion era.Clustering systems are used more and more often in text mining, especially in ...
Mohammad Eiman Jamnezhad, Reza Fattahi
doaj   +1 more source

K-means selected templates.

open access: yes, 2022
K-means selected templates.
Chi Zhang (9857)   +4 more
core   +1 more source

K-means algorithm [20].

open access: yes, 2023
K-means algorithm [20].
Nelly Rosario Moreno-Leyva (14341345)   +6 more
core   +1 more source

An Improved K-means Clustering Algorithm Towards an Efficient Data-Driven Modeling

open access: yesAnnals of Data Science, 2022
K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group.
M. Zubair   +5 more
semanticscholar   +1 more source

Multi-Swap k-Means++

open access: yesAdvances in Neural Information Processing Systems 36, 2023
The $k$-means++ algorithm of Arthur and Vassilvitskii (SODA 2007) is often the practitioners' choice algorithm for optimizing the popular $k$-means clustering objective and is known to give an $O(\log k)$-approximation in expectation. To obtain higher quality solutions, Lattanzi and Sohler (ICML 2019) proposed augmenting $k$-means++ with $O(k \log \log
Lorenzo Beretta 0001   +3 more
openaire   +3 more sources

Metode Boost-K-means untuk Clustering Puskesmas berdasarkan Persentase Bayi yang Diimunisasi

open access: yesJRST: Jurnal Riset Sains dan Teknologi, 2020
Dinas Kesehatan Kabupaten/Kota adalah satuan kerja pemerintahan daerah kabupaten/kota yang bertanggung jawab menyelenggarakan urusan pemerintahan dalam bidang kesehatan di kabupaten/kota.
Ahmad Irfan Abdullah   +2 more
doaj   +1 more source

YOLOv5-TS: Detecting traffic signs in real-time

open access: yesFrontiers in Physics, 2023
Traffic sign detection plays a vital role in assisted driving and automatic driving. YOLOv5, as a one-stage object detection solution, is very suitable for Traffic sign detection.
Jiquan Shen   +5 more
doaj   +1 more source

Group $K$-Means

open access: yesCoRR, 2015
The developed algorithm is similar with "Christopher F. Barnes, A new multiple path search technique for residual vector quantizers, 1994", but we conduct the research independently and apply it in data/feature compression and image ...
Jianfeng Wang   +5 more
openaire   +3 more sources

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