A5075375343- Rough Sets and Fuzzy Logic
- Data Mining Algorithms and Applications
- Text and Document Classification Technologies
- Multi-Criteria Decision Making
- Advanced Computational Techniques and Applications
- Face and Expression Recognition
- Machine Learning and Data Classification
- Image Retrieval and Classification Techniques
- Natural Language Processing Techniques
- Data Management and Algorithms
- Image Processing and 3D Reconstruction
- Mathematical Inequalities and Applications
- Advanced Decision-Making Techniques
- Grey System Theory Applications
- Data Stream Mining Techniques
- Imbalanced Data Classification Techniques
- Computational Drug Discovery Methods
- Evaluation Methods in Various Fields
- Advanced Research in Science and Engineering
- Advanced Algebra and Logic
- Optimization and Variational Analysis
- Advanced Algorithms and Applications
- Extenics and Innovation Methods
- Machine Learning in Bioinformatics
- Risk and Safety Analysis
Zhangzhou Normal University
2014-2024
Dalhousie University
2023
Hebei Normal University
2018-2020
Huaqiao University
2006
In the digital era, online platforms serve as crucial hubs for social interactions and idea exchange. However, these are continually shadowed by toxic comments that undermine genuine discourse have potential to harm participants. While machine learning provides an avenue detecting such content, a significant challenge arises when models, influenced biased training datasets, inadvertently propagate or amplify inherent biases. Such unintentional biases especially disconcerting they...
Attribute subset selection is an important issue in data mining and information processing. However, most automatic methodologies consider only the relevance factor between samples while ignoring diversity factor. This may not allow utilization value of hidden to be exploited. For this reason, we propose a hybrid model named intuitionistic fuzzy (IF) rough set overcome limitation. The combines technical advantages IF can effectively above-mentioned statistical factors. First, granules based...
Feature evaluation is an important issue in constructing a feature selection algorithm kernelized fuzzy rough sets, which has been proven to be effective approach deal with nonlinear classification tasks and uncertainty learning problems. However, the function developed sets cannot better reflect affinity relationship of samples time-consuming. To overcome these drawbacks, this article, problem studied based on spectral graph theory. First, within-class between-class sample similarity...
Label distribution learning (LDL) is a novel approach that outputs labels with varying degrees of description. To enhance the performance LDL algorithms, researchers have developed different algorithms mining label correlations globally, locally, and both globally locally. However, existing for local roughly assume samples within cluster share same correlations, which may not be applicable to all samples. Moreover, apply global parameter matrix, cannot fully exploit their respective...
Abstract Online streaming feature selection, as a well‐known and effective preprocessing approach in machine learning, is an eternal topic. Amount of online selection algorithms have achieved great deal success classification prediction tasks. However, most these existing only concentrate on the relevance between features labels, neglect causal relationships them. Discovering potential that is, Markov blanket (MB) class label, which can build more interpretable robust model. In this paper,...