Results 61 to 70 of about 1,981,824 (263)
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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Psychosocial Outcomes in Patients With Endocrine Tumor Syndromes: A Systematic Review
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction The combination of disease manifestations, the familial burden, and varying penetrance of endocrine tumor syndromes (ETSs) is unique. This review aimed to portray and summarize available data on psychosocial outcomes in patients with ETSs and explore gaps and opportunities for future research and care.
Daniël Zwerus +6 more
wiley +1 more source
Ilkom Jurnal Ilmiah, 2021 The coronavirus spreads quickly through human-to-human transmission via close contact and respiratory droplets such as coughing or sneezing. Various studies have been carried out to deal with Covid-19.
Wargijono Utomo
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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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Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Metabolic syndrome (MetS) is a common complication in survivors of childhood acute lymphoblastic and myeloid leukemia (AL), and a major risk factor for premature cardiovascular disease, type‐2‐diabetes, and metabolic dysfunction‐associated steatotic liver disease (MASLD).
Visentin Sandrine +10 more
wiley +1 more source
Towards explaining the speed of $k$-means [PDF]
, 2011 The $k$-means method is a popular algorithm for clustering, known for its speed in practice. This stands in contrast to its exponential worst-case running-time. To explain the speed of the $k$-means method, a smoothed analysis has been conducted.
Manthey, Bodo
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Solving $k$-means on High-dimensional Big Data
, 2015 In recent years, there have been major efforts to develop data stream algorithms that process inputs in one pass over the data with little memory requirement.
AK Jain +12 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga +56 more
wiley +1 more source
Profiling Academic Library Patrons using K-means and X-means Clustering
International Journal of Technology, 2019 Information technology is now used very often, especially by individuals born between 1982 and 2002 (the Millennial generation). The academic library, which from its beginnings has been a storehouse for information through collections, is becoming ...
Aisyah Larasati +5 more
doaj +1 more source