Výsledky vyhľadávania - Clustering—Algorithms General Terms Algorithms*

Clustering algorithms: A comparative approach Autor 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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Multiview Subspace Clustering Using Low-Rank Representation Autor Chen, Jie, Yang, Shengxiang, Mao, Hua, Fahy, Conor

“…Multiview subspace clustering is one of the most widely used methods for exploiting the internal structures of multiview data. Most previous studies have…”
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A seed-extended algorithm for detecting protein complexes based on density and modularity with topological structure and GO annotations Autor Wang, Rongquan, Wang, Caixia, Sun, Liyan, Liu, Guixia

“…Background The detection of protein complexes is of great significance for researching mechanisms underlying complex diseases and developing new drugs. Thus,…”
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Purely Contrastive Multiview Subspace Clustering Autor Wei, Lai, Li, Kexin, Zhou, Rigui, Liu, Jin

“… coefficient matrix in each view, and a contrastive alignment term to obtain a consensus coefficient matrix that fuses structural information from the reconstruction coefficient matrices…”
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Kullback-Leibler Divergence-Based Fuzzy C-Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation Autor Wang, Cong, Pedrycz, Witold, Li, Zhiwu, Zhou, Mengchu

“…). To make membership degrees of each image pixel closer to those of its neighbors, a KL divergence term on the partition matrix is introduced as a part of FCM, thus resulting in KL divergence-based FCM…”
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Stronger Convergence Results for the Center-Based Fuzzy Clustering With Convex Divergence Measure Autor Saha, Arkajyoti, Das, Swagatam

“…We present a novel alternative convergence theory of the fuzzy <inline-formula> <tex-math notation="LaTeX">C </tex-math></inline-formula>-means (FCM) clustering…”
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Improper Complex-Valued Bhattacharyya Distance Autor Mohammadi, Arash, Plataniotis, Konstantinos N.

“…Motivated by application of complex-valued signal processing techniques in statistical pattern recognition, classification, and Gaussian mixture (GM) modeling,…”
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A spatially focused clustering methodology for mining seismicity Autor Woodward, Kyle, Wesseloo, Johan, Potvin, Yves

“… The methodology presented in this article is developed from existing approaches that address the general limitations of density-based clustering algorithms…”
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In simulated data and health records, latent class analysis was the optimum multimorbidity clustering algorithm Autor Nichols, Linda, Taverner, Tom, Crowe, Francesca, Richardson, Sylvia, Yau, Christopher, Kiddle, Steven, Kirk, Paul, Barrett, Jessica, Nirantharakumar, Krishnarajah, Griffin, Simon, Edwards, Duncan, Marshall, Tom

“… We first investigated clustering algorithms in simulated datasets with 26 diseases of varying prevalence in predetermined clusters, comparing the derived clusters to known clusters using the adjusted Rand Index (aRI…”
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Lecture notes in data mining Autor Berry, Michael W, Browne, Murray

“…The continual explosion of information technology and the need for better data collection and management methods has made data mining an even more relevant…”
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Effectiveness of Environmental Cluster Analysis in Representing Regional Species Diversity Autor TRAKHTENBROT, ANA, KADMON, RONEN

“… We evaluated the performance of ECA with respect to two such decisions: the choice of the clustering algorithm…”
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Towards Efficient Clustering on Streaming Data Autor Zhang, Yu

“…Clustering is a fundamental data mining method for understanding and interpreting data. People apply clustering as an individual data analysis task or as one…”
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Structural k-means (S k-means) and clustering uncertainty evaluation framework (CUEF) for mining climate data Autor Doan, Quang-Van, Amagasa, Toshiyuki, Pham, Thanh-Ha, Sato, Takuto, Chen, Fei, Kusaka, Hiroyuki

“…Dramatic increases in climate data underlie a gradual paradigm shift in knowledge acquisition methods from physically based models to data-based mining…”
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General models for estimating daily global solar radiation for different solar radiation zones in mainland China Autor Li, Mao-Fen, Tang, Xiao-Ping, Wu, Wei, Liu, Hong-Bin

“…•Five solar radiation (Rs) zones were identified by long-term mean daily Rs.•Temperature- and sunshine-based models for Rs estimation were given for each site…”
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Capturing urban recreational hotspots from GPS data: A new framework in the lens of spatial heterogeneity Autor Shi, Haochen, Huang, Hao, Ma, Ding, Chen, Lu, Zhao, Miaoxi

“…Recreational activities are heterogeneously distributed throughout urban space, with far more low-density areas than high-density ones. Identification of…”
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Coherent signal localization with multiple arrays: a successive perspective Autor Zeng, Haowei, Shi, Sha, Yue, Heng, Li, Jianfeng

“… Then a coarse estimation is obtained by clustering algorithm, and a narrow search range can be determined for direct position determination (DPD) algorithm…”
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Embedding Clustering via Autoencoder and Projection onto Convex Set Autor Tran, Le-Anh, Nguyen, Thanh-Dat, Do, Truong-Dong, Tran, Chung Nguyen, Kwon, Daehyun, Park, Dong-Chul

“… This property of POCS has been applied to clustering analysis and the POCS-based clustering algorithm was proposed earlier…”
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Robust Suppressed Competitive Picture Fuzzy Clustering Driven by Entropy Autor Wu, Chengmao, Liu, Na

“…). The competitive learning regular term of the CAPFCM objective function is reinterpreted from the perspective of minimizing the entropy, and the general framework of the entropy…”
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Learning implicit user interest hierarchy for context in personalization Autor Kim, Hyoung-Rae, Chan, Philip K.

“…) algorithm to group terms (topics) into a hierarchy where more general interests are represented by a larger set of terms…”
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Robust clustering methods: a unified view Autor Dave, R.N., Krishnapuram, R.

“…Clustering methods need to be robust if they are to be useful in practice. In this paper, we analyze several popular robust clustering methods and show that…”
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