Author: Cai, Wei Xu Shengbing Zhang LiangJun Liu Jiongzhi Chen Peixuan
Title: Pairwise constraints cross entropy fuzzy clustering algorithm based on manifold learning and feature selection Cord-id: 53rgr2pm Document date: 2021_1_1
ID: 53rgr2pm
Snippet: In weakly supervised learning, it is difficult for us to utilize pairwise constraints information in feature selection. In order to solve the problem, we propose Pairwise constraints cross entropy fuzzy clustering algorithm based on manifold learning and feature selection (FCPC-LEFS). There are four phases in our approach: 1) Generate pseudo label;2) Dimension reduction by Laplacian Eigenmaps;3) Feature increment and selection;4) Cross-Entropy semi-Supervised Clustering Based on Pairwise Constra
Document: In weakly supervised learning, it is difficult for us to utilize pairwise constraints information in feature selection. In order to solve the problem, we propose Pairwise constraints cross entropy fuzzy clustering algorithm based on manifold learning and feature selection (FCPC-LEFS). There are four phases in our approach: 1) Generate pseudo label;2) Dimension reduction by Laplacian Eigenmaps;3) Feature increment and selection;4) Cross-Entropy semi-Supervised Clustering Based on Pairwise Constraints. We apply our approach to three UCI datasets and a COVID19-CT image dataset. Experiments show that our manifold learning and feature selection method are able to increase improve the clustering performance.
Search related documents:
Co phrase search for related documents- Try single phrases listed below for: 1
Co phrase search for related documents, hyperlinks ordered by date