User profiles for Pingxin Wang
Pingxin Wang( Wang P, 王平心)Jiangsu University of Science and Technology Verified email at just.edu.cn Cited by 974 |
CE3: A three-way clustering method based on mathematical morphology
Many existing clustering methods produce clusters with clear and sharp boundaries, which
does not truly reflect the fact that a cluster may not necessarily have a well-defined boundary …
does not truly reflect the fact that a cluster may not necessarily have a well-defined boundary …
Three-way k-means: integrating k-means and three-way decision
P Wang, H Shi, X Yang, J Mi�- …�journal of machine learning and cybernetics, 2019 - Springer
The traditional k-means, which unambiguously assigns an object precisely to a single cluster
with crisp boundary, does not adequately show the fact that a cluster may not have a well-…
with crisp boundary, does not adequately show the fact that a cluster may not have a well-…
Rough set based semi-supervised feature selection via ensemble selector
Similar to feature selection over completely labeled data, the aim of feature selection over
partially labeled data (semi-supervised feature selection) is also to find a feature subset which …
partially labeled data (semi-supervised feature selection) is also to find a feature subset which …
Granular ball guided selector for attribute reduction
In this study, a granular ball based selector was developed for reducing the dimensions of
data from the perspective of attribute reduction. The granular ball theory offers a data-adaptive …
data from the perspective of attribute reduction. The granular ball theory offers a data-adaptive …
A three-way adaptive density peak clustering (3W-ADPC) method
To address the difficulty of determining a clear-cut boundary of a cluster, three-way clustering
methods search for a new type of cluster structure characterized by a pair of a core region …
methods search for a new type of cluster structure characterized by a pair of a core region …
Three-way ensemble clustering for incomplete data
P Wang, X Chen�- IEEE Access, 2020 - ieeexplore.ieee.org
There are many incomplete data sets in all fields of scientific studies due to random noise,
data lost, limitations of data acquisition, data misunderstanding etc. Most of the clustering …
data lost, limitations of data acquisition, data misunderstanding etc. Most of the clustering …
Three-way clustering: Foundations, survey and challenges
Clustering, as an unsupervised data mining technique, allows us to classify similar objects
into the same cluster according to certain criteria. It helps us identify patterns between objects, …
into the same cluster according to certain criteria. It helps us identify patterns between objects, …
Fusing attribute reduction accelerators
Y Chen, X Yang, J Li, P Wang, Y Qian�- Information Sciences, 2022 - Elsevier
In the fields of rough set and machine learning, attribute reduction has been demonstrated
to be effective in removing redundant attributes with clear explanations. Therefore, not only …
to be effective in removing redundant attributes with clear explanations. Therefore, not only …
Attribution reduction based on sequential three-way search of granularity
Most existing results about attribute reduction are reported by considering one and only one
granularity, especially for the strategies of searching reducts. Nevertheless, how to derive …
granularity, especially for the strategies of searching reducts. Nevertheless, how to derive …
Accelerator for multi-granularity attribute reduction
By considering the information granulation in Granular Computing, the concept of the multi-granularity
is important. It is mainly because different results of information granulation will …
is important. It is mainly because different results of information granulation will …