Results 61 to 70 of about 2,006,480 (313)
Analyze the Clustering and Predicting Results of Palm Oil Production in Aceh Utara
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023 PT. Perkebunan Nusantara 1 is engaged in oil palm production with a total land area of 1,144 Ha. The formulation of this research can determine productive land clusters based on land area, number of trees, number of stages, and palm oil production ...
Mutammimul Ula +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 ...
openaire +2 more sources
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
core +2 more sources
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
core +1 more source
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
Using classification and K-means methods to predict breast cancer recurrence in gene expression data
Journal of Medical Signals and Sensors, 2022 Background: Breast cancer is a type of cancer that starts in the breast tissue and affects about 10% of women at different stages of their lives.
Mohammadreza Sehhati +3 more
doaj +1 more source
Randomized Dimensionality Reduction for k-means Clustering [PDF]
, 2013 We study the topic of dimensionality reduction for $k$-means clustering. Dimensionality reduction encompasses the union of two approaches: \emph{feature selection} and \emph{feature extraction}.
Boutsidis, Christos +3 more
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction We developed MedSupport, a multilevel medication adherence intervention designed to address root barriers to medication adherence. This study sought to explore the feasibility and acceptability of the MedSupport intervention strategies to support a future full‐scale randomized controlled trial.
Elizabeth G. Bouchard +8 more
wiley +1 more source