Model and Method for Constructing a Heterogeneous Cluster Ensemble

[1]  Wenqi Wei,et al.  Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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

[3]  Jiawei Han,et al.  Spectral Clustering , 2018, Data Clustering: Algorithms and Applications.

[4]  Vladimir B. Berikov,et al.  Ensemble clustering based on weighted co-association matrices: Error bound and convergence properties , 2017, Pattern Recognit..

[5]  M. Cugmas,et al.  On comparing partitions , 2015 .

[6]  Sandro Vega-Pons,et al.  A Survey of Clustering Ensemble Algorithms , 2011, Int. J. Pattern Recognit. Artif. Intell..

[7]  Joydeep Ghosh,et al.  Cluster ensembles , 2011, Data Clustering: Algorithms and Applications.

[8]  Anil K. Jain Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..

[9]  Ana L. N. Fred,et al.  Analysis of consensus partition in cluster ensemble , 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

[10]  Ludmila I. Kuncheva,et al.  Combining Pattern Classifiers: Methods and Algorithms , 2004 .

[11]  Yoav Freund,et al.  Boosting the margin: A new explanation for the effectiveness of voting methods , 1997, ICML.

[12]  P. Rousseeuw Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[13]  Sultan Noman Qasem,et al.  Cluster ensemble selection using balanced normalized mutual information , 2020, J. Intell. Fuzzy Syst..

[14]  L. Breiman Random Forests , 2001, Machine Learning.

[15]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[16]  V. Ryazanov On the synthesis of classifying algorithms in finite sets of classification algorithms (taxonomy) , 1982 .