Model Selection Strategies for Determining the Optimal Number of Overlapping Clusters in Additive Overlapping Partitional Clustering
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Model Selection Strategies for Determining the Optimal Number of Overlapping Clusters in Additive Overlapping Partitional Clustering
Authors
Keywords
-
Journal
JOURNAL OF CLASSIFICATION
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-01-17
DOI
10.1007/s00357-021-09409-1
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An improved overlapping k-means clustering method for medical applications
- (2017) Sina Khanmohammadi et al. EXPERT SYSTEMS WITH APPLICATIONS
- Overlapping Community Detection based on Network Decomposition
- (2016) Zhuanlian Ding et al. Scientific Reports
- Big Data and Network Biology
- (2014) Shigehiko Kanaya et al. Biomed Research International
- On the Advantage of Overlapping Clusters for Minimizing Conductance
- (2013) Rohit Khandekar et al. ALGORITHMICA
- Additive Biclustering: A Comparison of One New and Two Existing ALS Algorithms
- (2013) Tom F. Wilderjans et al. JOURNAL OF CLASSIFICATION
- Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective
- (2013) Kristopher J. Preacher et al. MULTIVARIATE BEHAVIORAL RESEARCH
- An algorithm based on density and compactness for dynamic overlapping clustering
- (2013) Airel Pérez-Suárez et al. PATTERN RECOGNITION
- Lowdimensional Additive Overlapping Clustering
- (2012) Dirk Depril et al. JOURNAL OF CLASSIFICATION
- Overlapping correlation clustering
- (2012) Francesco Bonchi et al. KNOWLEDGE AND INFORMATION SYSTEMS
- New trends on soft computing models in industrial and environmental applications
- (2012) Emilio Corchado et al. NEUROCOMPUTING
- Osom: A method for building overlapping topological maps
- (2012) Guillaume Cleuziou PATTERN RECOGNITION LETTERS
- Belief C-Means: An extension of Fuzzy C-Means algorithm in belief functions framework
- (2011) Zhun-ga Liu et al. PATTERN RECOGNITION LETTERS
- Consistent selection of the number of clusters via crossvalidation
- (2010) J. Wang BIOMETRIKA
- The CHull procedure for selecting among multilevel component solutions
- (2010) Eva Ceulemans et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- Graph-based data clustering with overlaps
- (2010) Michael R. Fellows et al. Discrete Optimization
- A Survey of Evolutionary Algorithms for Clustering
- (2009) E.R. Hruschka et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE
- Dynamic hierarchical algorithms for document clustering
- (2009) Reynaldo Gil-García et al. PATTERN RECOGNITION LETTERS
- Discriminating between strong and weak structures in three-mode principal component analysis
- (2008) Eva Ceulemans et al. BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY
- Algorithms for additive clustering of rectangular data tables
- (2008) Dirk Depril et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
- ECM: An evidential version of the fuzzy c-means algorithm
- (2007) Marie-Hélène Masson et al. PATTERN RECOGNITION
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now