Rough sets: probabilistic versus deterministic approach
International Journal of Man-Machine Studies
A decision-theoretic roguth set model
Methodologies for intelligent systems, 5
A decision theoretic framework for approximating concepts
International Journal of Man-Machine Studies
Variable precision rough set model
Journal of Computer and System Sciences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Extensions and intentions in the rough set theory
Information Sciences: an International Journal
Relational interpretations of neighborhood operators and rough set approximation operators
Information Sciences—Informatics and Computer Science: An International Journal
Analyzing the effectiveness and applicability of co-training
Proceedings of the ninth international conference on Information and knowledge management
A comparative study of fuzzy rough sets
Fuzzy Sets and Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Enhancing Supervised Learning with Unlabeled Data
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Experiments with Classifier Combining Rules
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Granulation and nearest neighborhoods: rough set approach
Granular computing
Co-training with a Single Natural Feature Set Applied to Email Classification
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
A tolerance rough set approach to clustering web search results
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
EROS: Ensemble rough subspaces
Pattern Recognition
Expert Systems with Applications: An International Journal
Attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Neighborhood rough set based heterogeneous feature subset selection
Information Sciences: an International Journal
Probabilistic rough set approximations
International Journal of Approximate Reasoning
Analyzing Co-training Style Algorithms
ECML '07 Proceedings of the 18th European conference on Machine Learning
Review: Dimensionality reduction based on rough set theory: A review
Applied Soft Computing
A comparison of two types of rough sets induced by coverings
International Journal of Approximate Reasoning
Monotonic Variable Consistency Rough Set Approaches
International Journal of Approximate Reasoning
Semi-supervised Rough Cost/Benefit Decisions
Fundamenta Informaticae - Fundamentals of Knowledge Technology
Three-way decisions with probabilistic rough sets
Information Sciences: an International Journal
Constructive and algebraic methods of the theory of rough sets
Information Sciences: an International Journal
Information-theoretic measures of uncertainty for rough sets and rough relational databases
Information Sciences: an International Journal
A comparative study of fuzzy sets and rough sets
Information Sciences: an International Journal
The investigation of the Bayesian rough set model
International Journal of Approximate Reasoning
Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications
International Journal of Approximate Reasoning
A rough set approach to classifying web page without negative examples
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Hybrid approaches to attribute reduction based on indiscernibility and discernibility relation
International Journal of Approximate Reasoning
Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Tolerance Approximation Spaces
Fundamenta Informaticae
An efficient rough feature selection algorithm with a multi-granulation view
International Journal of Approximate Reasoning
Matroidal structure of rough sets and its characterization to attribute reduction
Knowledge-Based Systems
International Journal of Approximate Reasoning
Rough matroids based on relations
Information Sciences: an International Journal
Incorporating logistic regression to decision-theoretic rough sets for classifications
International Journal of Approximate Reasoning
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Rough set theory is an effective supervised learning model for labeled data. However, it is often the case that practical problems involve both labeled and unlabeled data, which is outside the realm of traditional rough set theory. In this paper, the problem of attribute reduction for partially labeled data is first studied. With a new definition of discernibility matrix, a Markov blanket based heuristic algorithm is put forward to compute the optimal reduct of partially labeled data. A novel rough co-training model is then proposed, which could capitalize on the unlabeled data to improve the performance of rough classifier learned only from few labeled data. The model employs two diverse reducts of partially labeled data to train its base classifiers on the labeled data, and then makes the base classifiers learn from each other on the unlabeled data iteratively. The classifiers constructed in different reduct subspaces could benefit from their diversity on the unlabeled data and significantly improve the performance of the rough co-training model. Finally, the rough co-training model is theoretically analyzed, and the upper bound on its performance improvement is given. The experimental results show that the proposed model outperforms other representative models in terms of accuracy and even compares favorably with rough classifier trained on all training data labeled.