Algorithms for clustering data
Algorithms for clustering data
Boolean Feature Discovery in Empirical Learning
Machine Learning
Proceedings of the sixth international workshop on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments
Machine Learning - Special issue on evaluating and changing representation
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Applying AI Clustering to Engineering Tasks
IEEE Expert: Intelligent Systems and Their Applications
Machine Learning
Efficient Feature Selection in Conceptual Clustering
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Iterative optimization and simplification of hierarchical clusterings
Journal of Artificial Intelligence Research
Proportional Membership in Fuzzy Clustering as a Model of Ideal Types
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Evidence Accumulation Clustering Based on the K-Means Algorithm
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Topic Discovery from Text Using Aggregation of Different Clustering Methods
AI '02 Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Finding Consistent Clusters in Data Partitions
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Data mining tasks and methods: Clustering: conceptual clustering
Handbook of data mining and knowledge discovery
A New Cluster Isolation Criterion Based on Dissimilarity Increments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dimensionality Reduction in Automatic Knowledge Acquisition: A Simple Greedy Search Approach
IEEE Transactions on Knowledge and Data Engineering
Feature Selection for Unsupervised Learning
The Journal of Machine Learning Research
Simultaneous Feature Selection and Clustering Using Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Multiple Clusterings Using Evidence Accumulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns from Clusters Using Reduct
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Towards supporting expert evaluation of clustering results using a data mining process model
Information Sciences: an International Journal
A new clustering algorithm for coordinate-free data
Pattern Recognition
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Based on a reinterpretation of the square-error criterion for classical clustering, a “separate-and-conquer” version of K-Means clustering is presented and a contribution weight is determined for each variable of every cluster. The weight is used to produceconjunctive concepts that describe clusters and to reduce or transform the variable (feature) space.