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Updated: Jun 2, 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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一般化强大的回归技术和适应性集群采样,以有效估计稀有和集群种群的平均种群数量

Mir Subzar1, Taghreed Alqurashi2, Deeksha Chandawat3

  • 1UIM (Unitedworld Institute of Management), Karnavati University, Gandhinagar Gujarat, India. subzarstat@gmail.com.

Scientific reports
|January 15, 2025
PubMed
概括

适应性集群采样 (ACS) 可以被异常值扭曲. 这项研究引入了新的适应性比率类型回归估计器,对异常值具有稳定性,使用各种M估计函数提高了罕见和集群群体的准确性.

关键词:
自适应集群采样 (ACS)一般化的强健回归.胡贝尔 M 胡贝尔 M 胡贝尔平均平方误差 平均平方误差在OLS回归过程中,

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