CVDD

版本 1.0 (826.6 KB) 作者: Lianyu Hu
An Internal Validity Index Based on Density-Involved Distance
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更新时间 2021/10/22
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An Internal Validity Index Based on Density-Involved Distance

https://ieeexplore.ieee.org/document/8672850

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Requirement

The source code is written by Matlab r2016a. Versions lower than Matlab r2012a have not been tested. View CVDD on File Exchange

Simplest Demo

  • RUN Ncut_test.m to determine the optimal partition from varied partitions (produced by Jianbo Shi's Normalized cuts).

    CVDD.m includes Algorithm 1: CVDD in our paper.

    Ncut_test.m as an example includes Algorithm 2: CVDD-OP in our paper.

    'OP_CA' (in Ncut_test.m) shows the comparison. [ Purity, CVDD, CVNN, WB, Silhouette, CH, DB, Dunn, S_Dbw, I ]

Parameters in CVDD

No need to tune.

Datasets used

File Datasets_all30 includes 10 non-spherical clusters, 10 spherical clusters and 10 classification datasets (real datasets) used in the experiments of our paper.

Issues, Questions, etc

Please report issues here on the github page or contact "hly4ml@gmail.com"

引用格式

Lianyu Hu (2024). CVDD (https://github.com/hulianyu/CVDD/releases/tag/v1.0), GitHub. 检索来源 .

Hu, Lianyu, and Caiming Zhong. An Internal Validity Index Based on Density-Involved Distance. Institute of Electrical and Electronics Engineers (IEEE), 2019, pp. 40038–51, doi:10.1109/access.2019.2906949.

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MATLAB 版本兼容性
创建方式 R2016a
与 R2012a 及更高版本兼容
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1.0

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。