Label iteration-based clustering ensemble algorithm
The existing training strategies for clustering ensemble algorithm are generally conducted based on the same data and different base clustering algorithms and commonly have the limitations of low performance for large-scale data and weak adaptability of consensus function. To address these problems,...
Saved in:
Main Authors: | HE Yulin, YANG Jin, HUANG Zhexue, YIN Jianfei |
---|---|
Format: | Article |
Language: | zho |
Published: |
POSTS&TELECOM PRESS Co., LTD
2024-12-01
|
Series: | 智能科学与技术学报 |
Subjects: | |
Online Access: | http://www.cjist.com.cn/zh/article/doi/10.11959/j.issn.2096-6652.202443/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Detecting Anomaly Classification Using PCA-Kmeans and Ensembled Classifier for Wind Turbines
by: Prince Waqas Khan, et al.
Published: (2024-01-01) -
Critical factors influencing live birth rates in fresh embryo transfer for IVF: insights from cluster ensemble algorithms
by: Zheng Yu, et al.
Published: (2025-01-01) -
Ensemble graph auto-encoders for clustering and link prediction
by: Chengxin Xie, et al.
Published: (2025-01-01) -
Advanced Credit Card Fraud Detection: An Ensemble Learning Using Random Under Sampling and Two-Stage Thresholding
by: Ibrahim Almubark
Published: (2024-01-01) -
Shale-pore Semantic Segmentation Network Based on Pseudo-labeling
by: Chenzhang WANG, et al.
Published: (2025-01-01)