Simulation studies are often used to compare different clustering methods, be it with the aim of promoting a new method, or for investigating the quality of existing methods from a neutral point of view. I will go through a number of aspects of designing and running such studies, including the definition and measurement of clustering quality, the choice of models to generate data from, aggregation and visualisation of results, and also limits of what we can learn from such studies. The paper may be useful for researchers who run such simulation studies and for those interested in the results of them. Some aspects are relevant for more general simulation studies, also outside the domain of cluster analysis
Many research papers have studied the problem of taking a set of data and separating it into subgrou...
<p>We simulated three cluster types: “common” (<i>Cluster pattern 1</i>), “nested” (<i>Cluster patte...
Cluster analysis consists of applying statistical and heuris-tic methods in an attempt to discover t...
Simulation studies are often used to compare different clustering methods, be it with the aim of pro...
<p>A, C, E) Example draws from each of three simulation scenarios (Gaussians, arcs & Gaussians, and ...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
In this paper, I describe a large variety of clustering methods within a single framework. This pape...
This paper deals with the question whether the quality of different clustering algorithms can be com...
<p>Simulation scenario 1 consists of a pair of matched data sets of 200 features (20 of which are re...
Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in ...
There are many algorithms to cluster sample data points based on nearness or a similar-ity measure. ...
The following mixture model-based clustering methods are compared in a simulation study with one-dim...
A framework for classifying clustering algorithms and a method for performing comparative analyses h...
(A) The clustering runtime vs. the number of cells in the simulated datasets for all four methods. (...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
Many research papers have studied the problem of taking a set of data and separating it into subgrou...
<p>We simulated three cluster types: “common” (<i>Cluster pattern 1</i>), “nested” (<i>Cluster patte...
Cluster analysis consists of applying statistical and heuris-tic methods in an attempt to discover t...
Simulation studies are often used to compare different clustering methods, be it with the aim of pro...
<p>A, C, E) Example draws from each of three simulation scenarios (Gaussians, arcs & Gaussians, and ...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
In this paper, I describe a large variety of clustering methods within a single framework. This pape...
This paper deals with the question whether the quality of different clustering algorithms can be com...
<p>Simulation scenario 1 consists of a pair of matched data sets of 200 features (20 of which are re...
Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in ...
There are many algorithms to cluster sample data points based on nearness or a similar-ity measure. ...
The following mixture model-based clustering methods are compared in a simulation study with one-dim...
A framework for classifying clustering algorithms and a method for performing comparative analyses h...
(A) The clustering runtime vs. the number of cells in the simulated datasets for all four methods. (...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
Many research papers have studied the problem of taking a set of data and separating it into subgrou...
<p>We simulated three cluster types: “common” (<i>Cluster pattern 1</i>), “nested” (<i>Cluster patte...
Cluster analysis consists of applying statistical and heuris-tic methods in an attempt to discover t...