Search Results - Clustering-algorithms General Terms Algorithms

Clustering algorithms: A comparative approach by Rodriguez, Mayra Z., Comin, Cesar H., Casanova, Dalcimar, Bruno, Odemir M., Amancio, Diego R., Costa, Luciano da F., Rodrigues, Francisco A.

“…Many real-world systems can be studied in terms of pattern recognition tasks, so that proper use (and understanding…”
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Comprehensive survey on hierarchical clustering algorithms and the recent developments by Ran, Xingcheng, Xi, Yue, Lu, Yonggang, Wang, Xiangwen, Lu, Zhenyu

“…Data clustering is a commonly used data processing technique in many fields, which divides objects into different clusters in terms of some similarity measure between data points…”
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Clustering algorithms based on correlation coefficients for probabilistic linguistic term sets by Lin, Mingwei, Wang, Huibing, Xu, Zeshui, Yao, Zhiqiang, Huang, Jinli

“… Therefore, some correlation coefficient formulas are put forward to measure the relationship between two PLTSs and then they are utilized to develop two novel clustering algorithms to group PLTSs in this paper…”
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Detecting and analysing the topology of the cosmic web with spatial clustering algorithms I: methods by Kelesis, Dimitrios, Basilakos, Spyros, Papadopoulou Lesta, Vicky, Fotakis, Dimitris, Efstathiou, Andreas

“…ABSTRACT In this paper, we explore the use of spatial clustering algorithms as a new computational approach for modelling the cosmic web…”
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A Novel Hybrid Technique of Integrating Gradient-Boosted Machine and Clustering Algorithms for Lithology Classification by Asante-Okyere, Solomon, Shen, Chuanbo, Ziggah, Yao Yevenyo, Rulegeya, Mercy Moses, Zhu, Xiangfeng

“…) to construct a more accurate gradient-boosted machine (GBM) lithology model. The findings of the study showed that improved performance in terms of classification accuracy rate was achieved by the K -means-based GBM classifiers…”
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A new hybrid optimization approach using PSO, Nelder-Mead Simplex and Kmeans clustering algorithms for 1D Full Waveform Inversion by Aguiar Nascimento, Rutinaldo, Neto, Álvaro Barroca, Bezerra, Yuri Shalom de Freitas, do Nascimento, Hugo Alexandre Dantas, Lucena, Liacir dos Santos, de Freitas, Joaquim Elias

“…). Therefore, we developed a two-phase hybrid optimization algorithm based on DFO algorithms…”
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Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials by Sinha, Pratik, Spicer, Alexandra, Delucchi, Kevin L, McAuley, Daniel F, Calfee, Carolyn S, Churpek, Matthew M

“…). Investigators have sought to identify heterogeneity of treatment effect (HTE) in RCTs using clustering algorithms…”
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Detecting IoT Anomalies Using Fuzzy Subspace Clustering Algorithms by Shenify, Mohamed, Mazarbhuiya, Fokrul Alom, Wungreiphi, A. S.

“…There are many applications of anomaly detection in the Internet of Things domain. IoT technology consists of a large number of interconnecting digital devices…”
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Computer-Aided Diagnosis of Duchenne Muscular Dystrophy Based on Texture Pattern Recognition on Ultrasound Images Using Unsupervised Clustering Algorithms and Deep Learning by Liao, Ai-Ho, Wang, Chih-Hung, Wang, Chong-Yu, Liu, Hao-Li, Chuang, Ho-Chiao, Tseng, Wei-Jye, Weng, Wen-Chin, Shih, Cheng-Ping, Tsui, Po-Hsiang

“…) was previously explored for the first time. The present study further used clustering algorithms for the texture reconstruction of ultrasound images of DMD data sets…”
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A critical analysis of state-of-the-art metagenomics OTU clustering algorithms by Bhat, Ashaq Hussain, Prabhu, Puniethaa, Balakrishnan, Kalpana

“… Operational taxonomic unit (OTU) clustering algorithms are the important tools to perform taxonomic profiling by grouping 16S rRNA sequence reads into OTU clusters…”
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Detecting Variability in Massive Astronomical Time-series Data. III. Variable Candidates in the SuperWASP DR1 Found by Multiple Clustering Algorithms and a Consensus Clustering Method by Shin, Min-Su, Chang, Seo-Won, Yi, Hahn, Kim, Dae-Won, Kim, Myung-Jin, Byun, Yong-Ik

“… Variations in the light curves are described in terms of nine variability features that are complementary to each…”
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Cross-Validation Approach to Evaluate Clustering Algorithms: An Experimental Study Using Multi-Label Datasets by Tarekegn, Adane Nega, Michalak, Krzysztof, Giacobini, Mario

“… with. Up till now, the evaluation methods for clustering algorithms have been used for determining the optimal number of clusters in the data, assessing the quality of clustering results through various…”
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Comparative Analysis of Clustering Algorithms and Moodle Plugin for Creation of Student Heterogeneous Groups in Online University Courses by Nalli, Giacomo, Amendola, Daniela, Perali, Andrea, Mostarda, Leonardo

“… While random formation saves time and resources, the student heterogeneity in terms of learning capabilities is not guaranteed…”
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A comparison of graph-based word sense induction clustering algorithms in a pseudoword evaluation framework by Cecchini, Flavio Massimiliano, Riedl, Martin, Fersini, Elisabetta, Biemann, Chris

“…This article presents a comparison of different Word Sense Induction (WS1) clustering algorithms on two novel pseudoword data sets of semantic-similarity and co…”
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Expertise-Structure and Risk-Appetite-Integrated Two-Tiered Collective Opinion Generation Framework for Large-Scale Group Decision Making by Chen, Zhen-Song, Zhang, Xuan, Rodriguez, Rosa M., Pedrycz, Witold, Martinez, Luis, Skibniewski, Miroslaw J.

“…). In general, the collective opinion generation framework entails the following three phases, which are clustering analysis, weighting clusters, and preference aggregation…”
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Sparse Subspace Clustering: Algorithm, Theory, and Applications by Elhamifar, E., Vidal, R.

“… In this paper, we propose and study an algorithm, called sparse subspace clustering, to cluster data points that lie in a union of low-dimensional subspaces…”
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Competitive clustering algorithms based on ultrametric properties by Fouchal, S., Ahat, M., Ben Amor, S., Lavallée, I., Bui, M.

“…► We proposed in this paper two novel competitive unsupervised clustering algorithms…”
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Exact Recovery in the General Hypergraph Stochastic Block Model by Zhang, Qiaosheng, Tan, Vincent Y. F.

“…This paper investigates fundamental limits of exact recovery in the general d -uniform hypergraph stochastic block model ( d -HSBM…”
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Recombinator-k-Means: An Evolutionary Algorithm That Exploits k-Means++ for Recombination by Baldassi, Carlo

“…We introduce an evolutionary algorithm called recombinator-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means for optimizing the highly nonconvex kmeans problem…”
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General Type-2 Fuzzy C-Means Algorithm for Uncertain Fuzzy Clustering by Linda, O., Manic, M.

“… The focus of this paper is the management of uncertainty associated with parameters of fuzzy clustering algorithms. Type-2 fuzzy sets (T2 FSs…”
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