Results 71 to 80 of about 17,769,086 (225)
SimpleMKKM: Simple Multiple Kernel K-Means
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 We propose a simple yet effective multiple kernel clustering algorithm, termed simple multiple kernel k-means (SimpleMKKM). It extends the widely used supervised kernel alignment criterion to multi-kernel clustering.
Xinwang Liu
semanticscholar +1 more source
BarekengPopulation data is an important piece of information that is useful for regional planning and development. Insight into the state of an area is more straightforward to observe if there are grouped sub-districts.
Denny Nurdiansyah +4 more
doaj +1 more source
Deep k-Means: Jointly clustering with k-Means and learning representations
Pattern Recognition Letters, 2020 Under consideration at Pattern Recognition ...
Moradi Fard, Maziar +2 more
openaire +4 more sources
Application of Machine Learning-Based K-means Clustering for Financial Fraud Detection
Academic Journal of Science and TechnologyIn today's increasingly digital financial landscape, the frequency and complexity of fraudulent activities are on the rise, posing significant risks and losses for both financial institutions and consumers.
Zengyi Huang +3 more
semanticscholar +1 more source
Metode Elbow dan K-Means Guna Mengukur Kesiapan Siswa SMK Dalam Ujian Nasional
Jurnal Teknologi dan Sistem Informasi, 2020 Keberhasilan siswa dalam menempuh ujian nasional (UN) dapat terlihat dari perolehan nilai mata pelajaran yang diujikan, tiga diantaranya adalah nilai matematika, Bahasa Indonesia, dan Bahasa Inggris.
Ninik Tri Hartanti
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Barekeng, 2023 Scientific publication is a measure of the performance of a university. Universities that are owned and operated by the government and whose establishment is carried out by the President of Republic Indonesia are state universities (PTN).
Ermawati Ermawati +2 more
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A parametric k-means algorithm [PDF]
Computational Statistics, 2007 The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution.
openaire +3 more sources
Scientific ReportsThis study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering.
Manoharan Premkumar +7 more
semanticscholar +1 more source
Fast k-means based on KNN Graph
, 2017 In the era of big data, k-means clustering has been widely adopted as a basic processing tool in various contexts. However, its computational cost could be prohibitively high as the data size and the cluster number are large.
Deng, Cheng-Hao, Zhao, Wan-Lei
core +1 more source
Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), 2020 Melakukan pemilihan lahan tanam pada suatu lahan yang akan ditanami dengan kriteria lahan tanam yang sesuai sangat diperlukan sebagai pendukung keputusan. Kesalahan dalam memilih lokasi lahan tanam yang tidak sesuai membuat menurunnya produksi kentang di
Khomsatun Khomsatun +3 more
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