Results 51 to 60 of about 2,020,211 (266)
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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Outcomes of Live Virus Vaccination in Patients With Vascular Anomalies Being Treated With Sirolimus
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Live vaccination in patients with vascular anomalies (VA) receiving sirolimus remains controversial due to immunosuppressive effects and theoretical risks. Procedure This single‐center retrospective study included patients with VA less than 4 years old at the start of sirolimus therapy who were incompletely vaccinated.
Svatava Merkle +5 more
wiley +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
Kernel Probabilistic K-Means Clustering
Sensors, 2021 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
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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.
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Fast Approximate $K$-Means via Cluster Closures
, 2012 $K$-means, a simple and effective clustering algorithm, is one of the most widely used algorithms in multimedia and computer vision community. Traditional $k$-means is an iterative algorithm---in each iteration new cluster centers are computed and each ...
Ke, Qifa +4 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Kaposiform lymphangiomatosis (KLA) is an aggressive complex lymphatic anomaly. Patients exhibit malformed lymphatic vessels and often develop hemorrhagic effusions and elevated angiopoietin‐2 (Ang‐2) levels. A somatic NRAS p.Q61R (NRASQ61R) mutation has been associated with KLA.
C. Griffin McDaniel +3 more
wiley +1 more source
Customer analytics for online retailers using weighted k-means and RFM analysis
Data Analytics and Applied Mathematics, 2023 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
BOOTSTRAPPING K-MEANS CLUSTERING
Journal of the Japanese Society of Computational Statistics, 1990 Summary: Independent observations \(X_ 1,X_ 2,\ldots,X_ n\) are made on a distribution \(F\) on \(R^ d\). To divide these observations into \(k\) clusters, first choose a vector of optimal cluster centers \(b_ n=(b_{n1},b_{n2},\ldots,b_{nk})\) to minimize \(W_ n(a)=n^{- 1}\sum^ n_{i=1}\min_{1\leq j\leq k}\| X_ i-a_ j\|^ 2\) as a function of \(a=(a_ 1 ...
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Faster K-Means Cluster Estimation
, 2017 There has been considerable work on improving popular clustering algorithm `K-means' in terms of mean squared error (MSE) and speed, both. However, most of the k-means variants tend to compute distance of each data point to each cluster centroid for ...
A Likas, DT Pham, SP Lloyd, T Kanungo
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