scispace - formally typeset
Open AccessJournal ArticleDOI

Silhouettes: a graphical aid to the interpretation and validation of cluster analysis

Reads0
Chats0
TLDR
A new graphical display is proposed for partitioning techniques, where each cluster is represented by a so-called silhouette, which is based on the comparison of its tightness and separation, and provides an evaluation of clustering validity.
About
This article is published in Journal of Computational and Applied Mathematics.The article was published on 1987-11-01 and is currently open access. It has received 14144 citations till now. The article focuses on the topics: Silhouette & Dunn index.

read more

Citations
More filters
Journal ArticleDOI

Comprehensive Integration of Single-Cell Data.

TL;DR: A strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities.
Journal ArticleDOI

Comprehensive molecular characterization of human colon and rectal cancer

Donna M. Muzny, +320 more
- 19 Jul 2012 - 
TL;DR: Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.
Journal ArticleDOI

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
References
More filters

Some methods for classification and analysis of multivariate observations

TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
Journal ArticleDOI

Hierarchical Grouping to Optimize an Objective Function

TL;DR: In this paper, a procedure for forming hierarchical groups of mutually exclusive subsets, each of which has members that are maximally similar with respect to specified characteristics, is suggested for use in large-scale (n > 100) studies when a precise optimal solution for a specified number of groups is not practical.
Journal ArticleDOI

Hierarchical clustering schemes

TL;DR: A useful correspondence is developed between any hierarchical system of such clusters, and a particular type of distance measure, that gives rise to two methods of clustering that are computationally rapid and invariant under monotonic transformations of the data.
Journal ArticleDOI

Numerical methods for fuzzy clustering

TL;DR: In this paper, the authors considered the problem of decomposition of the probability density function of the original set into the weighted sum of the component fuzzy set densities, which is done by optimization of some functional defined over all possible fuzzy classifications.
Related Papers (5)