Results 61 to 70 of about 11,198,889 (292)
New bounds for $k$-means and information $k$-means
In this paper, we derive a new dimension-free non-asymptotic upper bound for the quadratic $k$-means excess risk related to the quantization of an i.i.d sample in a separable Hilbert space. We improve the bound of order $\mathcal{O} \bigl( k / \sqrt{n} \bigr)$ of Biau, Devroye and Lugosi, recovering the rate $\sqrt{k/n}$ that has already been proved by
Appert, Gautier, Catoni, Olivier
openaire +2 more sources
ABSTRACT Background Establishing a comprehensive apheresis medicine program in a resource‐constrained setting presents significant structural, financial, and logistical challenges. Despite the growing clinical importance of apheresis services globally, published experience from sub‐Saharan Africa remains sparse.
Folasade Adelekan‐Popoola +4 more
wiley +1 more source
ABSTRACT Background Maintenance hemodialysis (MHD) patients frequently suffer from frailty, characterized by reduced physical function and poor prognosis. Myokines, such as myonectin, secreted by muscle, are emerging regulators of systemic health. This study investigated the relationship between serum myonectin, adipokines (adiponectin, omentin), and ...
Kenichi Kono +7 more
wiley +1 more source
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Population 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
Soil data clustering by using K-means and fuzzy K-means algorithm
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
doaj +1 more source
Kernel Probabilistic K-Means Clustering
Kernel fuzzy c-means (KFCM) is a significantly improved version of fuzzy c-means (FCM) for processing linearly inseparable datasets. However, for fuzzification parameter m=1, the problem of KFCM (kernel fuzzy c-means) cannot be solved by Lagrangian ...
Bowen Liu +4 more
doaj +1 more source
Balanced K-Means for Clustering [PDF]
We present a k-means-based clustering algorithm, which optimizes mean square error, for given cluster sizes. A straightforward application is balanced clustering, where the sizes of each cluster are equal. In k-means assignment phase, the algorithm solves the assignment problem by Hungarian algorithm.
Malinen Mikko, Fränti Pasi
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ABSTRACT Introduction This final analysis of a multicenter, prospective postmarketing surveillance study evaluated the safety of daprodustat in patients with chronic kidney disease anemia in routine clinical practice in Japan. Methods Patients who initiated daprodustat between September 2020 and July 2022 were registered.
Tadao Akizawa +7 more
wiley +1 more source
Customer analytics for online retailers using weighted k-means and RFM analysis
In recent years, there has been a significant trend toward data-driven enterprises in the business world. This trend is exemplified by the frustration reported by 74% of customers when they encounter ads that are not relevant to them, as reported by ...
Ahmed Mohamed Ahmed Serwah +3 more
doaj +1 more source

