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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 +2 more
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Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce [PDF]
, 2014 The kernel $k$-means is an effective method for data clustering which extends the commonly-used $k$-means algorithm to work on a similarity matrix over complex data structures.
Elgohary, Ahmed +3 more
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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
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CLUSTERING KABUPATEN BERDASARKAN LUAS HUTAN MENGGUNAKAN METODE K-MEANS DI PROVINSI JAWA TENGAH
Jurnal Teknologi Industri Pertanian, 2023 Indonesia is one of the countries with the largest forest in the world. The tropical climate and high rainfall cause a lot of biodiversity in Indonesia’s forests. The existence of these forests can be utilized by many parties, both the government and the
Yusri Eli Hotman Turnip , Rina Fitriana
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PYTHON MÜHİTİNDƏ K-MEANS, K-MEANS++ VƏ MİNİ BATCH K-MEANS ALQORİTMLƏRİNİN MÜQAYİSƏLİ ANALİZİ
Problems of Information Technology, 2021 Məqalədə k-means alqortitmi və onun modifikasiyalarının Python mühitində müxtəlif ölçülü verilənlərə tətbiqi məsələlərinə baxılır. Eyni zamanda ənənəvi k-means klasterləşdirmə alqoritmi və onun modifikasıyalarının mövcud vəziyyəti, imkanları, çatışmazlıqları, meydana çıxan problemlər tədqiq edilmiş və onların həlli üçün təkliflər verilmişdir. k-means++
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Clustering with Spectral Norm and the k-means Algorithm [PDF]
, 2010 There has been much progress on efficient algorithms for clustering data points generated by a mixture of $k$ probability distributions under the assumption that the means of the distributions are well-separated, i.e., the distance between the means of ...
Kannan, Ravindran, Kumar, Amit
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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 +3 more
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, 2018 The recent framework of compressive statistical learning aims at designing tractable learning algorithms that use only a heavily compressed representation-or sketch-of massive datasets.
Jacques, Laurent, Schellekens, Vincent
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Privacy-Preserving and Outsourced Multi-User k-Means Clustering [PDF]
, 2014 Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Often, the entities involved in the data mining process are end-users or organizations with limited computing and storage resources.
Bertino, Elisa +4 more
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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 +2 more
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