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Stock Data Clustering of Food and Beverage Company

IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2007
Cluster analysis can be defined as identifying groups of similar objects to discover distribution of patterns and interesting correlations in large data sets.
Shofwatul Uyun, Subanar Subanar
doaj   +1 more source

MODIFIKASI K-MEANS BERBASIS ORDERED WEIGHTED AVERAGING (OWA) UNTUK KASUS KLASTERING

Agrointek, 2016
K-means clustering method based on Ordered Weighted Averaging (OWA) was developed by Cheng et al (2009) to resolve problem in classification using integrating k-means clustering and OWA.
Millatul Ulya Millatul Ulya
doaj  

Approximation Algorithms for Bregman Co-clustering and Tensor Clustering

, 2008
In the past few years powerful generalizations to the Euclidean k-means problem have been made, such as Bregman clustering [7], co-clustering (i.e., simultaneous clustering of rows and columns of an input matrix) [9,18], and tensor clustering [8,34 ...
Banerjee, Arindam, Jegelka, Stefanie, Sra, Suvrit   +2 more
core   +1 more source

Enhancing the performance of gradient boosting trees on regression problems

Journal of Big Data
Gradient Boosting Trees (GBT) is a powerful machine learning technique that is based on ensemble learning methods that leverage the idea of boosting. GBT combines multiple weak learners sequentially to boost its prediction power proving its outstanding ...
Lydia Wahid Rizkallah
doaj   +1 more source

Total Jensen divergences: Definition, Properties and k-Means++ Clustering

, 2013
We present a novel class of divergences induced by a smooth convex function called total Jensen divergences. Those total Jensen divergences are invariant by construction to rotations, a feature yielding regularization of ordinary Jensen divergences by a ...
Nielsen, Frank, Nock, Richard
core  

Research on Automatic Alignment for Corn Harvesting Based on Euclidean Clustering and K-Means Clustering

Agriculture
Aiming to meet the growing need for automated harvesting, an automatic alignment method based on Euclidean clustering and K-means clustering is proposed to address issues of driver fatigue and inaccurate driving in manually operated corn harvesters ...
Bin Zhang, Hao Xu, Kunpeng Tian, Jicheng Huang, Fanting Kong, Senlin Mu, Teng Wu, Zhongqiu Mu, Xingsong Wang, Deqiang Zhou   +9 more
doaj   +1 more source

A cross dataset meta-model for hepatitis C detection using multi-dimensional pre-clustering

Scientific Reports
Hepatitis C is a liver infection triggered by the hepatitis C virus (HCV). The infection results in swelling and irritation of the liver, which is called inflammation. Prolonged untreated exposure to the virus can lead to chronic hepatitis C.
Aryan Sharma, Tanmay Khade, Shashank Mouli Satapathy   +2 more
doaj   +1 more source

Pediatric asthma population risk stratification using k-means clustering. [PDF]

J Asthma
Rezaeiahari M, Eyimina A, Boyd M, Brown CC, Perry TT, Ararat E, Tilford JM, Jefferson AA.   +7 more
europepmc   +1 more source

Visual field prediction using K-means clustering in patients with primary open angle glaucoma. [PDF]

Int J Ophthalmol
Lee J, Kim J, Kim H, Moon S, Kim E, Jeong S, Yang H, Lee J.   +7 more
europepmc   +1 more source

Construction of automatic air monitoring point siting model based on convolutional neural network and K-means clustering. [PDF]

Sci Rep
Liu S, Peng J, He X.
europepmc   +1 more source