Clustering incomplete relational data using the non-Euclidean relational fuzzy c-means algorithm
Pattern Recognition Letters
Some Notes on Alternating Optimization
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
A generalized feedforward neural network architecture for classification and regression
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm
Neural Processing Letters
A Hybrid Neural Network System for Pattern Classification Tasks with Missing Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Missing Value Estimation For Microarray Data Based On Fuzzy C-means Clustering
HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
Imputing incomplete time-series data based on varied-window similarity measure of data sequences
Pattern Recognition Letters
Computer Vision and Image Understanding
A fast fuzzy clustering algorithm
AIKED'07 Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases - Volume 6
On the efficiency of evolutionary fuzzy clustering
Journal of Heuristics
Fuzzy cluster stability analysis with missing values using resampling
International Journal of Bioinformatics Research and Applications
Knowledge Base Extraction for Fuzzy Diagnosis of Mental Retardation Level
Proceedings of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium
Clustering: A neural network approach
Neural Networks
Differentiated treatment of missing values in fuzzy clustering
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Collaborative optimization of clustering by fuzzy c-means and weight determination by ReliefF
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
A fuzzy c-means clustering algorithm based on nearest-neighbor intervals for incomplete data
Expert Systems with Applications: An International Journal
Clustering dictionary definitions using Amazon Mechanical Turk
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Fuzzy clustering of incomplete data based on cluster dispersion
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
An efficient approach to clustering real-estate listings
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Multi-group QoS consensus for web services
Journal of Computer and System Sciences
Missing data analysis with fuzzy C-Means: A study of its application in a psychological scenario
Expert Systems with Applications: An International Journal
UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: applications and services - Volume Part IV
Iterative clustering analysis for grouping missing data in gene expression profiles
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Weighted fuzzy c-means clustering based on double coding genetic algorithm
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Handling incomplete categorical data for supervised learning
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Gradient-Based FCM and a neural network for clustering of incomplete data
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Data Envelopment Analysis of clinics with sparse data: Fuzzy clustering approach
Computers and Industrial Engineering
Fuzzy data mining: a literature survey and classification framework
International Journal of Networking and Virtual Organisations
On cluster validity for fuzzy clustering of incomplete data
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Fuzzy Cluster Validation Based on Fuzzy PCA-Guided Procedure
International Journal of Fuzzy System Applications
Random walk distances in data clustering and applications
Advances in Data Analysis and Classification
Consensus strategy for clustering using RC-images
Pattern Recognition
Clustering with Missing Values
Fundamenta Informaticae
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The problem of clustering a real s-dimensional data set X={x1 ,…,xn} ⊂ Rs is considered. Usually, each observation (or datum) consists of numerical values for all s features (such as height, length, etc.), but sometimes data sets can contain vectors that are missing one or more of the feature values. For example, a particular datum xk might be incomplete, having the form xk=(254.3, ?, 333.2, 47.45, ?)T, where the second and fifth feature values are missing. The fuzzy c-means (FCM) algorithm is a useful tool for clustering real s-dimensional data, but it is not directly applicable to the case of incomplete data. Four strategies for doing FCM clustering of incomplete data sets are given, three of which involve modified versions of the FCM algorithm. Numerical convergence properties of the new algorithms are discussed, and all approaches are tested using real and artificially generated incomplete data sets