The complexity of Boolean functions
The complexity of Boolean functions
On changing continuous attributes into ordered discrete attributes
EWSL-91 Proceedings of the European working session on learning on Machine learning
Machine learning: an artificial intelligence approach volume III
Machine learning: an artificial intelligence approach volume III
C4.5: programs for machine learning
C4.5: programs for machine learning
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Dynamic Reducts as a Tool for Extracting Laws from Decisions Tables
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
On Finding Optimal Discretizations for Two Attributes
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
A Method to Find Learner's Key Characteristic in Wed-Based Learning
ICWL '08 Proceedings of the 7th international conference on Advances in Web Based Learning
Invariants Discretization for Individuality Representation in Handwritten Authorship
IWCF '08 Proceedings of the 2nd international workshop on Computational Forensics
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Rough sets for solving classification problems in computational neuroscience
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Transactions on rough sets XII
A supervised and multivariate discretization algorithm for rough sets
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Core-generating discretization for rough set feature selection
Transactions on rough sets XIII
A vague-rough set approach for uncertain knowledge acquisition
Knowledge-Based Systems
Approximate boolean reasoning approach to rough sets and data mining
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
A divide-and-conquer discretization algorithm
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Approximate boolean reasoning: foundations and applications in data mining
Transactions on Rough Sets V
Feature selection with test cost constraint
International Journal of Approximate Reasoning
| Hi-index | 0.00 |
We study the relationship between reduct problem in Rough Sets theory and the problem of real value attribute discretization. We consider the problem of searching for a minimal set of cuts on attribute domains that preserves discernibility of objects with respect to any chosen attributes subset of cardinality s (where s is a parameter given by a user). Such a discretization procedure assures that one can keep all reducts consisting of at least s attributes. We show that this optimization problem is NP-hard and it is interesting to find efficient heuristics for solving this problem.