Assessing the robustness of cluster solutions obtained from sparse count matrices.

Psychological Methods ◽

10.1037/met0000204 ◽

2019 ◽

Vol 24 (6) ◽

pp. 675-689 ◽

Author(s):

Kathleen M. Gates ◽

Zachary F. Fisher ◽

Cara Arizmendi ◽

Teague R. Henry ◽

Kelly A. Duffy ◽

...

Keyword(s):

Cluster Solutions

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Symmetry, Hopf bifurcation, and the emergence of cluster solutions in time delayed neural networks

Chaos An Interdisciplinary Journal of Nonlinear Science ◽

10.1063/1.5006921 ◽

2017 ◽

Vol 27 (11) ◽

pp. 114316 ◽

Author(s):

Zhen Wang ◽

Sue Ann Campbell

Keyword(s):

Neural Networks ◽

Hopf Bifurcation ◽

Delayed Neural Networks ◽

Cluster Solutions

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Dynamical Properties of Hierarchical Polymeric Cluster Solutions

Relaxation in Complex Systems and Related Topics - NATO ASI Series ◽

10.1007/978-1-4899-2136-9_30 ◽

1990 ◽

pp. 223-230 ◽

Author(s):

M. Delsanti ◽

J. P. Munch ◽

M. Adam ◽

D. Durand

Keyword(s):

Dynamical Properties ◽

Cluster Solutions ◽

Polymeric Cluster

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Evaluation of structure and reproducibility of cluster solutions using the bootstrap

Marketing Letters ◽

10.1007/s11002-009-9083-4 ◽

2009 ◽

Vol 21 (1) ◽

pp. 83-101 ◽

Author(s):

Sara Dolnicar ◽

Friedrich Leisch

Keyword(s):

Cluster Solutions

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Exact Traveling Cluster Solutions of Differential Equations with Delay for a Traffic Flow Model

Traffic and Granular Flow ’99 ◽

10.1007/978-3-642-59751-0_43 ◽

2008 ◽

pp. 413-418

Author(s):

K. Hasebe ◽

A. Nakayama ◽

Y. Sugiyama

Keyword(s):

Differential Equations ◽

Traffic Flow ◽

Traffic Flow Model ◽

Cluster Solutions ◽

Equations With Delay

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A Light Middleware for Client-Cluster Solutions

BIS 2000 ◽

10.1007/978-1-4471-0761-3_11 ◽

2000 ◽

pp. 172-180

Author(s):

Alexei Zabrodin

Keyword(s):

Cluster Solutions

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A novel fuzzy C-means algorithm to generate diverse and desirable cluster solutions used by genetic-based clustering ensemble algorithms

Memetic Computing ◽

10.1007/s12293-012-0073-3 ◽

2012 ◽

Vol 4 (1) ◽

pp. 49-71 ◽

Author(s):

Reza Ghaemi ◽

Md. Nasir Sulaiman ◽

Hamidah Ibrahim ◽

Norwati Mustapha

Keyword(s):

Clustering Ensemble ◽

Fuzzy C Means ◽

Cluster Solutions ◽

Ensemble Algorithms ◽

Fuzzy C Means Algorithm

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Fast vector quantizer on neural clustering networks providing globally optimal cluster solutions

Proceedings of 13th International Conference on Pattern Recognition ◽

10.1109/icpr.1996.547444 ◽

1996 ◽

Author(s):

U. Moller ◽

M. Galicki ◽

H. Witte

Keyword(s):

Vector Quantizer ◽

Neural Clustering ◽

Cluster Solutions ◽

Optimal Cluster

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Stability of cluster solutions in a cooperative consumer chain model

Journal of Mathematical Biology ◽

10.1007/s00285-012-0616-8 ◽

2012 ◽

Vol 68 (1-2) ◽

pp. 1-39 ◽

Author(s):

Juncheng Wei ◽

Matthias Winter

Keyword(s):

Chain Model ◽

Cluster Solutions

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Stability of two cluster solutions in pulse coupled networks of neural oscillators

Journal of Computational Neuroscience ◽

10.1007/s10827-010-0268-x ◽

2010 ◽

Vol 30 (2) ◽

pp. 427-445 ◽

Author(s):

Lakshmi Chandrasekaran ◽

Srisairam Achuthan ◽

Carmen C. Canavier

Keyword(s):

Neural Oscillators ◽

Coupled Networks ◽

Cluster Solutions

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Some Algorithms for the Computation of Independent Cluster Solutions

Perceptual and Motor Skills ◽

10.2466/pms.1977.45.3f.1135 ◽

1977 ◽

Vol 45 (3_suppl) ◽

pp. 1135-1142

Author(s):

Richard J. Hofmann

Keyword(s):

Cluster Solution ◽

Alternative Algorithm ◽

Algebraic Framework ◽

Cluster Solutions

The Harris and Kaiser algorithm for computing independent cluster solutions is discussed and an alternative algorithm is presented. Both algorithms are presented within the context of a general algebraic framework for ideal orthogonal and oblique independent cluster solutions. Finally an example is presented whereby the alternative algorithm defines a better approximation to an ideal independent cluster solution than does Harris and Kaiser's algorithm.

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