Three-way approximations fusion with granular-ball computing to guide multi-granularity fuzzy entropy for feature selection
D **a, G Wang, Q Zhang, J Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In large-scale decision systems with high dimensions, constructing an efficient feature
selection method via an uncertainty measure, has become a critical problem in fuzzy rough …
selection method via an uncertainty measure, has become a critical problem in fuzzy rough …
Granular-conditional-entropy-based attribute reduction for partially labeled data with proxy labels
Attribute reduction is attracting considerable attention in the theory of rough sets, and thus
many rough-set-based attribute reduction methods have been presented. However, most of …
many rough-set-based attribute reduction methods have been presented. However, most of …
Feature selection using relative dependency complement mutual information in fitting fuzzy rough set model
J Xu, X Meng, K Qu, Y Sun, Q Hou - Applied Intelligence, 2023 - Springer
As a reliable and valid tool for analyzing uncertain information, fuzzy rough set theory has
attracted widespread concern in feature selection. However, the performance of fuzzy rough …
attracted widespread concern in feature selection. However, the performance of fuzzy rough …
Imbalanced data classification based on diverse sample generation and classifier fusion
J Zhai, J Qi, S Zhang - International Journal of Machine Learning and …, 2022 - Springer
Class imbalance problems are pervasive in many real-world applications, yet classifying
imbalanced data remains to be a very challenging task in machine learning. SMOTE is the …
imbalanced data remains to be a very challenging task in machine learning. SMOTE is the …
Quickly calculating reduct: An attribute relationship based approach
Presently, attribute reduction, as one of the most important topics in the field of rough set,
has been widely explored from different perspectives. To derive the qualified reduct defined …
has been widely explored from different perspectives. To derive the qualified reduct defined …
Spark rough hypercuboid approach for scalable feature selection
Feature selection refers to choose an optimal non-redundant feature subset with minimal
degradation of learning performance and maximal avoidance of data overfitting. The …
degradation of learning performance and maximal avoidance of data overfitting. The …