Results 11 to 20 of about 938,196 (259)

$k$-means clustering of extremes [PDF]

Electronic Journal of Statistics, 2019
The $k$-means clustering algorithm and its variant, the spherical $k$-means clustering, are among the most important and popular methods in unsupervised learning and pattern detection.
Janßen, Anja, Wan, Phyllis
core   +7 more sources

Fast k-means algorithm clustering

International journal of Computer Networks & Communications, 2011
k-means has recently been recognized as one of the best algorithms for clustering unsupervised data. Since k-means depends mainly on distance calculation between all data points and the centers, the time cost will be high when the size of the dataset is ...
Kecman, Vojislav, Li, Qi, Salman, Raied, Strack, Robert, Test, Erik   +4 more
core   +2 more sources

Transformed K-means Clustering [PDF]

2021 29th European Signal Processing Conference (EUSIPCO), 2021
EUSIPCO ...
Goel, Anurag, Majumdar, Angshul
openaire   +2 more sources

RSKC: An R Package for a Robust and Sparse K-Means Clustering Algorithm

Journal of Statistical Software, 2016
Witten and Tibshirani (2010) proposed an algorithim to simultaneously find clusters and select clustering variables, called sparse K-means (SK-means).
Yumi Kondo, Matias Salibian-Barrera, Ruben Zamar   +2 more
doaj   +1 more source

Penerapan Algoritma K-Means Untuk Mengklasifikasi Data Obat

Jurnal Sisfokom, 2023
Pengklasifikasian data obat pada sebuah instansi yang bergerak pada bidang Kesehatan merupakan hal yang sangat penting. Kegiatan tersebut tidak lepas dari pengawasan serta monitoring setiap harinya karena pengolahan data obat termasuk inti dalam ...
Ferdy Pangestu Ferdy Pangestu, Nur Yasin Nur Yasin, Ronald Chistover Ronald Chistover Hasugian, yunita yunita   +3 more
doaj   +1 more source

K-MEANS WITH SAMPLING FOR DETERMINING PROMINENT COLORS IN IMAGES

ICTACT Journal on Soft Computing, 2022
A tool that quickly calculates the dominant colors of an image can be very useful in image processing. The k-means clustering algorithm has this potential since it partitions a set of data into n clusters and returns a representative data point from each
Angelina Cheng, Eric Rosenberg, Alina Gorbunova   +2 more
doaj   +1 more source

Technology Topic Mining and Trend Analysis from the Perspective of Industrial Chain Combined with K-Means and LDA——Taking Virtual Reality Technology as an Example

Zhishi guanli luntan, 2020
[Purpose/significance] From the perspective of industry chain, this paper takes virtual reality technology as an example, constructs VR patent industry chain corpus, and explores the technical theme, research and development hotspot and future ...
Chen Ling, Lin Ping, Duan Yaoqing
doaj   +1 more source

Clustering Productive Palm Land using the K- Means Clustering Algorithm

Journal of Innovation Information Technology and Application, 2023
Indonesia is a country with a tropical climate that has many oil palm plantations. CV. Alkema Deo is one of the companies that manage oil palm plantations in Sampit City, East Kotawaringin Regency, Central Kalimantan. CV.
Geofanny Widianto Sihite, Eka Prasetyaningrum   +1 more
doaj   +1 more source

Merging $K$-means with hierarchical clustering for identifying general-shaped groups [PDF]

, 2017
Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and $K$-means clustering are two approaches but have different strengths and weaknesses.
Ghosh, Arka P., Maitra, Ranjan, Peterson, Anna D.   +2 more
core   +4 more sources

On Variants of k-means Clustering [PDF]

, 2015
\textit{Clustering problems} often arise in the fields like data mining, machine learning etc. to group a collection of objects into similar groups with respect to a similarity (or dissimilarity) measure.
Bandyapadhyay, Sayan, Varadarajan, Kasturi   +1 more
core   +2 more sources