D. Davies, и D. Bouldin. IEEE Trans. Pattern Anal. Mach. Intell., 1 (2):
224-227(1979)
Аннотация
A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster.
The measure can be used to infer the appropriateness of data partitions and can therefore be used to compare relative appropriateness of various divisions of the data. The measure does not depend on either the number of clusters analysed nor the method of partitioning of the data and can be used to guide a cluster seeking algorithm.
%0 Journal Article
%1 journals/pami/DaviesB79
%A Davies, David L.
%A Bouldin, Donald W.
%D 1979
%J IEEE Trans. Pattern Anal. Mach. Intell.
%K clustering evaluation lecture:2016 lecture:data-mining measure
%N 2
%P 224-227
%T A Cluster Separation Measure
%V 1
%X A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster.
The measure can be used to infer the appropriateness of data partitions and can therefore be used to compare relative appropriateness of various divisions of the data. The measure does not depend on either the number of clusters analysed nor the method of partitioning of the data and can be used to guide a cluster seeking algorithm.
@article{journals/pami/DaviesB79,
abstract = {A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster.
The measure can be used to infer the appropriateness of data partitions and can therefore be used to compare relative appropriateness of various divisions of the data. The measure does not depend on either the number of clusters analysed nor the method of partitioning of the data and can be used to guide a cluster seeking algorithm.},
added-at = {2016-04-25T21:22:03.000+0200},
author = {Davies, David L. and Bouldin, Donald W.},
biburl = {https://www.bibsonomy.org/bibtex/22d1c60bbc64ed61cd5937e5d18ea5628/nosebrain},
ee = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.1979.4766909},
interhash = {4d8d95b0c12d888337ae3da6ea10d780},
intrahash = {2d1c60bbc64ed61cd5937e5d18ea5628},
journal = {IEEE Trans. Pattern Anal. Mach. Intell.},
keywords = {clustering evaluation lecture:2016 lecture:data-mining measure},
number = 2,
pages = {224-227},
timestamp = {2016-04-25T21:25:07.000+0200},
title = {A Cluster Separation Measure},
volume = 1,
year = 1979
}