标题
Interpretable fuzzy clustering using unsupervised fuzzy decision trees
作者
关键词
-
出版物
INFORMATION SCIENCES
Volume 611, Issue -, Pages 540-563
出版商
Elsevier BV
发表日期
2022-08-27
DOI
10.1016/j.ins.2022.08.077
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A clustering- and maximum consensus-based model for social network large-scale group decision making with linguistic distribution
- (2022) Peide Liu et al. INFORMATION SCIENCES
- Clustering based on local density peaks and graph cut
- (2022) Zhiguo Long et al. INFORMATION SCIENCES
- EGMM: An evidential version of the Gaussian mixture model for clustering
- (2022) Lianmeng Jiao et al. APPLIED SOFT COMPUTING
- An Agglomerative Hierarchical Clustering Algorithm for Linear Ordinal Rankings
- (2021) Nana Liu et al. INFORMATION SCIENCES
- An oversampling algorithm combining SMOTE and k-means for imbalanced medical data
- (2021) Zhaozhao Xu et al. INFORMATION SCIENCES
- Deep Multi-view Document Clustering with Enhanced Semantic Embedding
- (2021) Ruina Bai et al. INFORMATION SCIENCES
- Fuzzy graph clustering
- (2021) Yong Peng et al. INFORMATION SCIENCES
- Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering
- (2021) Yaoming Cai et al. INFORMATION SCIENCES
- Efficient implementation and parallelization of fuzzy density based clustering
- (2021) Can Atilgan et al. INFORMATION SCIENCES
- Multi-level and relevance-based parallel clustering of massive data streams in smart manufacturing
- (2021) Ada Bagozi et al. INFORMATION SCIENCES
- A new robust fuzzy c-means clustering method based on adaptive elastic distance
- (2021) Yunlong Gao et al. KNOWLEDGE-BASED SYSTEMS
- Explaining smartphone-based acoustic data in bipolar disorder: Semi-supervised fuzzy clustering and relative linguistic summaries
- (2021) Katarzyna Kaczmarek-Majer et al. INFORMATION SCIENCES
- A Web service clustering method based on topic enhanced Gibbs sampling algorithm for the Dirichlet Multinomial Mixture model and service collaboration graph
- (2021) Qiang Hu et al. INFORMATION SCIENCES
- Design of Granular Model: A Method Driven by Hyper-Box Iteration Granulation
- (2021) Wei Lu et al. IEEE Transactions on Cybernetics
- Improved Clustering Algorithms for Image Segmentation Based on Non-local Information and Back Projection
- (2020) Xiaofeng Zhang et al. INFORMATION SCIENCES
- Interpretable clustering: an optimization approach
- (2020) Dimitris Bertsimas et al. MACHINE LEARNING
- BLOCK-DBSCAN: Fast clustering for large scale data
- (2020) Yewang Chen et al. PATTERN RECOGNITION
- SMKFC-ER: Semi-supervised multiple kernel fuzzy clustering based on entropy and relative entropy
- (2020) Fariba Salehi et al. INFORMATION SCIENCES
- TSF-DBSCAN: A Novel Fuzzy Density-Based Approach for Clustering Unbounded Data Streams
- (2020) Alessio Bechini et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Fuzzy Clustering: A Historical Perspective
- (2019) Enrique H. Ruspini et al. IEEE Computational Intelligence Magazine
- Online Clique Clustering
- (2019) Marek Chrobak et al. ALGORITHMICA
- Clustering nominal data using unsupervised binary decision trees: Comparisons with the state of the art methods
- (2017) Badih Ghattas et al. PATTERN RECOGNITION
- A rapid fuzzy rule clustering method based on granular computing
- (2014) Xianchang Wang et al. APPLIED SOFT COMPUTING
- Relative entropy fuzzy c-means clustering
- (2013) M. Zarinbal et al. INFORMATION SCIENCES
- Hesitant fuzzy agglomerative hierarchical clustering algorithms
- (2013) Xiaolu Zhang et al. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
- Interpretable clustering using unsupervised binary trees
- (2013) Ricardo Fraiman et al. Advances in Data Analysis and Classification
- FRBC: A Fuzzy Rule-Based Clustering Algorithm
- (2011) Eghbal G. Mansoori IEEE TRANSACTIONS ON FUZZY SYSTEMS
- SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
- (2008) Eghbal G. Mansoori et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now