Results 11 to 20 of about 1,846,894 (263)
Discriminative cluster analysis [PDF]
Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006 Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of programming and because it accomplishes a good trade-off between achieved performance and computational complexity.
Torre, Fernando De la, Kanade, Takeo
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Core Collection Formation in Guatemalan Wild Avocado Germplasm with Phenotypic and SSR Data
Agronomy, 2023 Guatemala’s wild avocado germplasm holds vital genetic value, but lacking conservation strategies imperils it. Studying its diversity is pivotal for conservation and breeding.
José Alejandro Ruiz-Chután +6 more
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, 2000 As an explorative technique, duster analysis provides a description or a reduction in the dimension of the data. It classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of many variables. Its aim is to construct groups in such a way that the profiles of objects in the same groups are relatively ...
Mucha, Hans-Joachim, Sofyan, Hizir
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Classification of Financial Events and Its Effects on Other Financial Data
Axioms, 2023 This research classifies financial events, i.e., the collapse of the Lehman Brothers (2008) and the flash crash (2010), and their effects on two different stocks corresponding to Citigroup Inc.
Maria C. Mariani +4 more
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Research on coal rock recognition algorithm and “self-learning” model
Meikuang Anquan, 2021 Aiming at the problems of poor effect, poor stability and small application range of coal and rock recognition methods in fully mechanized coal mining face, based on the difference between the basic characteristics of coal and rock, from the visual ...
ZHANG Wei, FU Yuan, LIU Xin
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Initial Cluster Analysis [PDF]
Journal of Computational Biology, 2018 We study a simple abstract problem motivated by a variety of applications in protein sequence analysis. Consider a string of 0s and 1s of length L, and containing D 1s. If we believe that some or all of the 1s may be clustered near the start of the sequence, which subset is the most significantly so clustered, and how significant is this clustering? We
Altschul, Stephen F., Neuwald, Andrew F.
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Consensus clustering and functional interpretation of gene-expression data [PDF]
, 2004 Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters.
Kellam, P. +6 more
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CES Transactions on Electrical Machines and Systems, 2019 Effective storage, processing and analyzing of power device condition monitoring data faces enormous challenges. A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun ...
Hongtao Shen, Peng Tao, Pei Zhao, Hao Ma
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Entropy, 2020 Over the last decades, load forecasting is used by power companies to balance energy demand and supply. Among the several load forecasting methods, medium-term load forecasting is necessary for grid’s maintenance planning, settings of electricity ...
Omaji Samuel +6 more
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Remote Sensing, 2022 Solar resource assessment is of paramount importance in the planning of solar energy applications. Solar resources are abundant and characterization is essential for the optimal design of a system. Solar energy is estimated, indirectly, by the processing
Jared D. Salinas-González +8 more
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