(A) The clustering runtime vs. the number of cells in the simulated datasets for all four methods. (B) The memory usage vs. the number of cells in the simulated datasets for all four methods. (C) The estimated number of clusters vs. the number of cells in the simulated datasets for three out of four methods: Secuer, Louvain and Leiden. k: thousand, M: million.</p
The graybox indicates that the memory of laptop was exceeded for large datasets when using other alg...
<p>The clustering and gene selection results for the four set-ups with , in terms of the average fre...
The k-means algorithm is a widely used clustering tech-nique. Here we will examine the performance o...
(A) The NMI of different methods on simulated datasets with different sample sizes. The simulated da...
<p>Computation Time in the stages of: (a) scaled down data clustering, (b) extend to all data cluste...
<p>A, C, E) Example draws from each of three simulation scenarios (Gaussians, arcs & Gaussians, and ...
(A) The clustering time of different methods. (B) The ARI of different methods on three large datase...
a<p>The number of clusters in the network is determined automatically by the algorithms.</p>b<p>The ...
<p>Simulation scenario 1 consists of a pair of matched data sets of 200 features (20 of which are re...
<p>This constitute simulation of three large data sets in the order of; 10,000×50, 30,000×50 and 50,...
<p>Average Rand indexes over all small replicates are indicated for each method and each model along...
All artificial datasets were used for evaluation. The averages were calculated separately for datase...
<p>The plots represent the comparison of five different methods of finding optimum number of cluster...
Simulation studies are often used to compare different clustering methods, be it with the aim of pro...
<p>The accuracy summary for the cluster assignment is based on 50 simulated datasets under each mode...
The graybox indicates that the memory of laptop was exceeded for large datasets when using other alg...
<p>The clustering and gene selection results for the four set-ups with , in terms of the average fre...
The k-means algorithm is a widely used clustering tech-nique. Here we will examine the performance o...
(A) The NMI of different methods on simulated datasets with different sample sizes. The simulated da...
<p>Computation Time in the stages of: (a) scaled down data clustering, (b) extend to all data cluste...
<p>A, C, E) Example draws from each of three simulation scenarios (Gaussians, arcs & Gaussians, and ...
(A) The clustering time of different methods. (B) The ARI of different methods on three large datase...
a<p>The number of clusters in the network is determined automatically by the algorithms.</p>b<p>The ...
<p>Simulation scenario 1 consists of a pair of matched data sets of 200 features (20 of which are re...
<p>This constitute simulation of three large data sets in the order of; 10,000×50, 30,000×50 and 50,...
<p>Average Rand indexes over all small replicates are indicated for each method and each model along...
All artificial datasets were used for evaluation. The averages were calculated separately for datase...
<p>The plots represent the comparison of five different methods of finding optimum number of cluster...
Simulation studies are often used to compare different clustering methods, be it with the aim of pro...
<p>The accuracy summary for the cluster assignment is based on 50 simulated datasets under each mode...
The graybox indicates that the memory of laptop was exceeded for large datasets when using other alg...
<p>The clustering and gene selection results for the four set-ups with , in terms of the average fre...
The k-means algorithm is a widely used clustering tech-nique. Here we will examine the performance o...