Cluster ensemble of valid small clusters

[1]  Hamid Parvin,et al.  An optimization algorithm based on behavior of see-see partridge chicks , 2017, J. Intell. Fuzzy Syst..

[2]  Hamid Parvin,et al.  To improve the quality of cluster ensembles by selecting a subset of base clusters , 2014, J. Exp. Theor. Artif. Intell..

[3]  Fang Liu,et al.  Spectral Clustering Ensemble Applied to SAR Image Segmentation , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Joydeep Ghosh,et al.  Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions , 2002, J. Mach. Learn. Res..

[5]  Xuegang Mao,et al.  Object-based forest gaps classification using airborne LiDAR data , 2018, Journal of Forestry Research.

[6]  Tossapon Boongoen,et al.  Comparative study of matrix refinement approaches for ensemble clustering , 2013, Machine Learning.

[7]  William F. Punch,et al.  Data weighing mechanisms for clustering ensembles , 2013, Comput. Electr. Eng..

[8]  Hamid Parvin,et al.  A new classifier ensemble methodology based on subspace learning , 2013, J. Exp. Theor. Artif. Intell..

[9]  Ira Assent,et al.  MultiClust special issue on discovering, summarizing and using multiple clusterings , 2014, Machine Learning.

[10]  Hamid Parvin,et al.  Clustering ensemble selection considering quality and diversity , 2015, Artificial Intelligence Review.

[11]  Hamid Parvin,et al.  Diverse classifier ensemble creation based on heuristic dataset modification , 2018 .

[12]  Muhammad Yousefnezhad,et al.  Wisdom of Crowds cluster ensemble , 2016, Intell. Data Anal..

[13]  Sos S. Agaian,et al.  A new acute leukaemia-automated classification system , 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

[14]  Yun Yang,et al.  Temporal Data Clustering via Weighted Clustering Ensemble with Different Representations , 2011, IEEE Transactions on Knowledge and Data Engineering.

[15]  Hamid Parvin,et al.  A clustering ensemble framework based on elite selection of weighted clusters , 2013, Adv. Data Anal. Classif..

[16]  Hamid Parvin,et al.  Proposing a classifier ensemble framework based on classifier selection and decision tree , 2015, Eng. Appl. Artif. Intell..

[17]  Steven Furnell,et al.  D-FICCA: A density-based fuzzy imperialist competitive clustering algorithm for intrusion detection in wireless sensor networks , 2014 .

[18]  Jane You,et al.  Hybrid Fuzzy Cluster Ensemble Framework for Tumor Clustering from Biomolecular Data , 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[19]  Alireza Aminsharifi,et al.  Artificial Neural Network System to Predict the Postoperative Outcome of Percutaneous Nephrolithotomy. , 2017, Journal of endourology.

[20]  Ana L. N. Fred,et al.  Combining multiple clusterings using evidence accumulation , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Huan Liu,et al.  Topic taxonomy adaptation for group profiling , 2008, TKDD.

[22]  Hamid Parvin,et al.  Consensus Function Based on Clusters Clustering and Iterative Fusion of Base Clusters , 2019, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[23]  Vipin Kumar,et al.  Chameleon: Hierarchical Clustering Using Dynamic Modeling , 1999, Computer.

[24]  Alessandro Laio,et al.  Clustering by fast search and find of density peaks , 2014, Science.

[25]  Hamid Parvin,et al.  A fuzzy clustering ensemble based on cluster clustering and iterative Fusion of base clusters , 2019, Applied intelligence (Boston).

[26]  Hamid Parvin,et al.  Cluster ensemble selection based on a new cluster stability measure , 2014, Intell. Data Anal..

[27]  Jitendra Malik,et al.  Normalized Cuts and Image Segmentation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  James C. Bezdek,et al.  On cluster validity for the fuzzy c-means model , 1995, IEEE Trans. Fuzzy Syst..

[29]  Yun Yang,et al.  Hybrid Sampling-Based Clustering Ensemble With Global and Local Constitutions , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[30]  Hamid Parvin,et al.  A comprehensive study of clustering ensemble weighting based on cluster quality and diversity , 2017, Pattern Analysis and Applications.

[31]  Aristides Gionis,et al.  Clustering aggregation , 2005, 21st International Conference on Data Engineering (ICDE'05).

[32]  Hamid Parvin,et al.  A clustering ensemble framework based on selection of fuzzy weighted clusters in a locally adaptive clustering algorithm , 2013, Pattern Analysis and Applications.

[33]  Lawrence O. Hall,et al.  A scalable framework for cluster ensembles , 2009, Pattern Recognit..

[34]  Tossapon Boongoen,et al.  A Link-Based Approach to the Cluster Ensemble Problem , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  William F. Punch,et al.  Effects of resampling method and adaptation on clustering ensemble efficacy , 2011, Artificial Intelligence Review.

[36]  Joachim M. Buhmann,et al.  Bagging for Path-Based Clustering , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Hamid Parvin,et al.  An artificial intelligence-based clinical decision support system for large kidney stone treatment , 2019, Australasian Physical & Engineering Sciences in Medicine.

[38]  Jingsheng Lei,et al.  A clustering ensemble: Two-level-refined co-association matrix with path-based transformation , 2015, Pattern Recognit..

[39]  Joshua Zhexue Huang,et al.  Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values , 1998, Data Mining and Knowledge Discovery.

[40]  Hamid Parvin,et al.  Dependability‐based cluster weighting in clustering ensemble , 2020, Stat. Anal. Data Min..

[41]  Yuchou Chang,et al.  Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm , 2008, Pattern Recognit..

[42]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[43]  Hamid Parvin,et al.  Explicit memory based ABC with a clustering strategy for updating and retrieval of memory in dynamic environments , 2018, Applied Intelligence.

[44]  Hamid Parvin,et al.  Dynamic protein–protein interaction networks construction using firefly algorithm , 2017, Pattern Analysis and Applications.

[45]  Shahaboddin Shamshirband,et al.  Developing a fuzzy clustering model for better energy use in farm management systems , 2015 .

[46]  Mohsen Moradi,et al.  CMCABC: Clustering and Memory-Based Chaotic Artificial Bee Colony Dynamic Optimization Algorithm , 2018, Int. J. Inf. Technol. Decis. Mak..

[47]  Wei Tang,et al.  Clusterer ensemble , 2006, Knowl. Based Syst..

[48]  Zhiwen Yu,et al.  Adaptive Noise Immune Cluster Ensemble Using Affinity Propagation , 2015, IEEE Transactions on Knowledge and Data Engineering.

[49]  Hamid Parvin,et al.  Elite fuzzy clustering ensemble based on clustering diversity and quality measures , 2018, Applied Intelligence.

[50]  Chang-Dong Wang,et al.  Combining multiple clusterings via crowd agreement estimation and multi-granularity link analysis , 2014, Neurocomputing.

[51]  Hamid Parvin,et al.  A linear unsupervised transfer learning by preservation of cluster-and-neighborhood data organization , 2018, Pattern Analysis and Applications.

[52]  Tossapon Boongoen,et al.  A Link-Based Cluster Ensemble Approach for Categorical Data Clustering , 2012, IEEE Transactions on Knowledge and Data Engineering.

[53]  Chang-Dong Wang,et al.  Ensemble clustering using factor graph , 2016, Pattern Recognit..

[54]  Fei Liu,et al.  Method for Determining the Optimal Number of Clusters Based on Agglomerative Hierarchical Clustering , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[55]  Hamid Parvin,et al.  Parkinson Detection: An Image Processing Approach , 2017 .

[56]  Dewayany Sutrisno,et al.  A feasibility study of seabed cover classification standard in generating related geospatial data , 2019, Geo spatial Inf. Sci..

[57]  Zengyou He,et al.  A cluster ensemble method for clustering categorical data , 2005, Information Fusion.

[58]  Ertunc Erdil,et al.  Combining multiple clusterings using similarity graph , 2011, Pattern Recognit..

[59]  Hamid Parvin,et al.  Using sub-sampling and ensemble clustering techniques to improve performance of imbalanced classification , 2018, Neurocomputing.

[60]  Ludmila I. Kuncheva,et al.  Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[61]  Hamid Parvin,et al.  Optimizing Fuzzy Cluster Ensemble in String Representation , 2013, Int. J. Pattern Recognit. Artif. Intell..

[62]  Hamid Parvin,et al.  Imputing missing value through ensemble concept based on statistical measures , 2018, Knowledge and Information Systems.

[63]  Hamid Parvin,et al.  Diversity based cluster weighting in cluster ensemble: an information theory approach , 2019, Artificial Intelligence Review.

[64]  Hamid Parvin,et al.  An innovative linear unsupervised space adjustment by keeping low-level spatial data structure , 2018, Knowledge and Information Systems.

[65]  James C. Bezdek,et al.  Some new indexes of cluster validity , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[66]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[67]  S. Nejatian,et al.  Gene Regulatory Elements Extraction in Breast Cancer by Hi-C Data Using a Meta-Heuristic Method , 2019, Russian Journal of Genetics.

[68]  Nikos A. Vlassis,et al.  The global k-means clustering algorithm , 2003, Pattern Recognit..

[69]  Hamid Parvin,et al.  Optimisation inspiring from behaviour of raining in nature: droplet optimisation algorithm , 2018, Int. J. Bio Inspired Comput..

[70]  Zhi-Hua Zhou,et al.  Ensemble Methods: Foundations and Algorithms , 2012 .

[71]  Benjamin King.  Step-Wise Clustering Procedures , 1967 .

[72]  Arindam Banerjee,et al.  Bayesian cluster ensembles , 2011, Stat. Anal. Data Min..

[73]  Anil K. Jain,et al.  Clustering ensembles: models of consensus and weak partitions , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.