Open AccessBook
Algorithms for clustering data
Anil K. Jain,Richard C. Dubes +1 more
Reads0
Chats0
About:
The article was published on 1988-01-01 and is currently open access. It has received 8586 citations till now. The article focuses on the topics: Cluster analysis & Correlation clustering.read more
Citations
More filters
Journal ArticleDOI
Rough Set Based Generalized Fuzzy $C$ -Means Algorithm and Quantitative Indices
Pradipta Maji,Sankar K. Pal +1 more
TL;DR: The RFPCM comprises a judicious integration of the principles of rough and fuzzy sets that incorporates both probabilistic and possibilistic memberships simultaneously to avoid the problems of noise sensitivity of fuzzy C-means and the coincident clusters of PCM.
Journal ArticleDOI
Application of metabolomics to plant genotype discrimination using statistics and machine learning
TL;DR: It is shown clearly that the two background lines can be discrimated between each other and their progeny, and indicated that theTwo progeny lines can also be discriminated.
Journal ArticleDOI
Bagging for path-based clustering
Bernd Fischer,Joachim M. Buhmann +1 more
TL;DR: A resampling scheme for clustering with similarity to bootstrap aggregation (bagging) is presented to improve the quality of path-based clustering, a data clustering method that can extract elongated structures from data in a noise robust way.
Journal ArticleDOI
Nearest q -flat to m points
TL;DR: In this article, the problem of finding the nearest q-flat to m points was extended to the general case, with 0 ≤ q≤q≤n−1.
Informal identification of outliers in medical data
TL;DR: The removal of outliers increased the descriptive classification accuracy of discriminant analysis functions and nearest neighbour method, while the predictive ability of these methods reduced somewhat.
References
More filters
Journal ArticleDOI
Shortest connection networks and some generalizations
TL;DR: In this paper, the basic problem of interconnecting a given set of terminals with a shortest possible network of direct links is considered, and a set of simple and practical procedures are given for solving this problem both graphically and computationally.
Journal ArticleDOI
An examination of procedures for determining the number of clusters in a data set
TL;DR: A Monte Carlo evaluation of 30 procedures for determining the number of clusters was conducted on artificial data sets which contained either 2, 3, 4, or 5 distinct nonoverlapping clusters to provide a variety of clustering solutions.
Journal ArticleDOI
SLINK: An optimally efficient algorithm for the single-link cluster method
TL;DR: Sibson gives an O(n 2) algorithm for single-linkage clustering, and proves that this algorithm achieves the theoretically optimal lower time bound for obtaining a single- linkage dendrogram.