相关实验视频

Updated: Jul 24, 2025

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

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基于分歧的局部加权集群集群与词典学习和L2,1-规范

Jiaxuan Xu1, Jiang Wu1, Taiyong Li1

  • 1School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China.

Entropy (Basel, Switzerland)
|July 8, 2023
PubMed
概括

本研究引入了一种新的基于分歧的局部加权集群集群与字典学习 (DLWECDL) 方法. 通过有效权重微集群和学习未标记数据的相似性矩阵,DLWECDL提高了集群准确性.

关键词:
在L2,1规范中,L2,1是标准.集群集成是指集群集成.词典学习学习词典学习整体集群集群是指集群集群.相似之处是相似之处.小空间聚类子空间聚类.

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