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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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2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 The Lloyd-Max algorithm is a classical approach to perform K-means clustering. Unfortunately, its cost becomes prohibitive as the training dataset grows large. We propose a compressive version of K-means (CKM), that estimates cluster centers from a sketch, i.e. from a drastically compressed representation of the training dataset.
Keriven, Nicolas +3 more
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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
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k-Means+++: Outliers-Resistant Clustering
, 2020 The k-means problem is to compute a set of k centers (points) that minimizes the sum of squared distances to a given set of n points in a metric space. Arguably, the most common algorithm to solve it is k-means++ which is easy to implement and provides a
Feldman, Dan +5 more
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Scalability of efficient parallel K-Means [PDF]
, 2009 Clustering is defined as the grouping of similar items in a set, and is an important process within the field of data mining. As the amount of data for various applications continues to increase, in terms of its size and dimensionality, it is necessary ...
Giuseppe Di Fatta +3 more
core +1 more source
Soil data clustering by using K-means and fuzzy K-means algorithm
Telfor Journal, 2016 A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering.
E. Hot, V. Popović-Bugarin
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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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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 +4 more sources