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Best clustering results (ACC±std) of various algorithms.

NIAID Data Ecosystem2026-03-11 收录

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https://figshare.com/articles/dataset/Best_clustering_results_ACC_std_of_various_algorithms_/11399127 数据链接链接失效反馈

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Best clustering results (ACC±std) of various algorithms.

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创建时间：

2019-12-18

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数据表示

This article provides a framework for assessing and quantifying “clusteredness” of a data representation. Clusteredness is a global univariate property defined as a layout diverging from equidistance

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Collection of news articles

文本数据

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Use this dataset for clustering textual data.

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Accountability simulator path planning data

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自动驾驶仿真

Measurement data of developed path planning algorithms. Regards execution time, path length and differences of conducted modifications.

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Assessing and Quantifying Clusteredness: The OPTICS Cordillera

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数据降维

DataCite Commons2025-05-01 更新40

Additional file 6 of Repeatability and reproducibility of the wzi high resolution melting-based clustering analysis for Klebsiella pneumoniae typing

微生物学

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Additional file 6: Table S6. Cross table of the clusters found in Perini et al. 2020b and the clusters of each instrument used in this work is reported. The discrepancies from the clusters found in Pe

DataCite Commons2020-12-21 更新20

Best clustering results (ACC±std) of various algorithms.

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