Results 11 to 20 of about 14,276,290 (299)
K-Means Cloning: Adaptive Spherical K-Means Clustering [PDF]
Algorithms, 2018 We propose a novel method for adaptive K-means clustering. The proposed method overcomes the problems of the traditional K-means algorithm. Specifically, the proposed method does not require prior knowledge of the number of clusters.
Abdel-Rahman Hedar +3 more
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Unsupervised K-Means Clustering Algorithm
IEEE Access, 2020 The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the
Kristina P. Sinaga, Miin-Shen Yang
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Spherical k-Means Clustering [PDF]
Journal of Statistical Software, 2012 Clustering text documents is a fundamental task in modern data analysis, requiring approaches which perform well both in terms of solution quality and computational efficiency.
Kurt Hornik +3 more
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t-k-means: A ROBUST AND STABLE k-means VARIANT [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 $k$-means algorithm is one of the most classical clustering methods, which has been widely and successfully used in signal processing. However, due to the thin-tailed property of the Gaussian distribution, $k$-means algorithm suffers from relatively poor performance on the dataset containing heavy-tailed data or outliers.
Yiming Li 0004 +5 more
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Exact Acceleration of K-Means++ and K-Means|| [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 K-Means++ and its distributed variant K-Means|| have become de facto tools for selecting the initial seeds of K-means. While alternatives have been developed, the effectiveness, ease of implementation,and theoretical grounding of the K-means++ and || methods have made them difficult to "best" from a holistic perspective.
openaire +3 more sources
Causal K-Means Clustering. [PDF]
J R Stat Soc Series B Stat MethodolAbstract Causal effects are often characterized at the population level, which can mask important heterogeneity across latent subgroups. Since the subgroup structure is unknown, identifying and evaluating subgroup specific effects is substantially more challenging than standard population level analysis.
Kim K, Kim J, Kennedy EH.
europepmc +4 more sources
Barekeng, 2021 Mengembangkan wilayah untuk mengurangi kesenjangan dan menjamin pemerataan merupakan salah satu dari tujuh agenda Pembangunana RPJMN IV Tahun 2020-2024. Setiap wilayah tentunya memiliki potensi yang berbeda, baik potensi fisik maupun non-fisik. Perbedaan
Muhamad Budiman Johra
doaj +1 more source
Skill set profile clustering: the empty K-means algorithm with automatic specification of starting cluster centers [PDF]
, 2010 While students’ skill set profiles can be estimated with formal cognitive diagnosis models [8], their computational complexity makes simpler proxy skill estimates attractive [1, 4, 6].
Nugent, R., Ayers, E., Dean, N.
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MathildeChen/PCA-K-means-for-PA-features: K-means-for-PA-features v0.1
, 2021 First release of the scripts used to identify profiles of movement behavior using k ...
MathildeCh3n
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