Summary table for the performance of clustering algorithms in datasets DB2C200F and DB10C200F.

Comparison of different normalization methods in term of clustering accuracy in percentage.

Haixuan Yang (147680)
Cathal Seoighe (2731)

October 2016

Reported is the mean of clustering accuracies from 100 runs of Basic NMF together with the standa...

Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets

Juan Carlos Perafan-Lopez
Valeria Lucía Ferrer-Gregory
César Nieto-Londoño
Julián Sierra-Pérez

June 2022

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for ...

Average clustering coefficient for varying N and MTE = 10×N.

Christine Largeron (727149)
Pierre-Nicolas Mougel (727150)
Reihaneh Rabbany (727151)
Osmar R. Zaïane (727152)

April 2015

Average clustering coefficient for varying N and MTE = 10×N.</p

Summary table for the performance of clustering algorithms in datasets DB2C2F and DB10C2F.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

ARIdef represents the average accuracy obtained when considering the default parameters of the algor...

Summary table for the performance of clustering algorithms in datasets DB2C10F and DB10C10F.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

ARIdef represents the average accuracy obtained when considering the default parameters of the algor...

Average performance of the seven considered clustering algorithms according to the number of features in the dataset.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

All artificial datasets were used for evaluation. The averages were calculated separately for datase...

Average performance of the seven considered clustering algorithms according to the number of objects per class in the dataset.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

All artificial datasets were used for evaluation. The averages were calculated separately for datase...

Performance of clustering algorithms on real-world data.

Esha Datta (16806608)
Aditya Ballal (16806611)
Javier E. López (4543504)
Leighton T. Izu (15431237)

August 2023

Shown are the NMI score and number of clusters (m′) predicted by MapperPlus, affinity propagation, D...

Performance of the algorithm for the cluster assignment.

Kai Yu (50223)
Sholom Wacholder (50226)
William Wheeler (186671)
Zhaoming Wang (50224)
Neil Caporaso (186673)
Maria Teresa Landi (89281)
Faming Liang (186676)

January 2012

The accuracy summary for the cluster assignment is based on 50 simulated datasets under each mode...

Performance of the algorithms when changing the expected number of clusters K in the dataset.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

The upper plots correspond to the ARI and Jaccard indices averaged for all datasets containing 10 cl...

Clustering Algorithms

Franěk, Dominik

January 2008

This work is an overview of some of the most frequently used algorithms for cluster analysis and som...

Performance for all classification algorithms over all peak picking and peak clustering algorithms and all replications for each dataset.

Salome Horsch (4436698)
Dominik Kopczynski (4436695)
Elias Kuthe (4436701)
Jörg Ingo Baumbach (671902)
Sven Rahmann (2715)
Jörg Rahnenführer (3861)

September 2017

Performance for all classification algorithms over all peak picking and peak clustering algorithm...

Average Adjusted Rand index to compare performances of clustering algorithms: k-means++, Qcut, kNN-Spectral and DBHT for the benchmark data sets collected by de Souto et al[40] (k++ indicates k-means++).

Won-Min Song (178326)
T. Di Matteo (178330)
Tomaso Aste (178337)

March 2012

The relatively high performing “Parameter given” results refer to cases when the true number of c...

Clustering-based performance of Dataset group #3 Gold Standard Datasets.

Ran Duan (821258)
Lin Gao (344965)
Yong Gao (29929)
Yuxuan Hu (398099)
Han Xu (68252)
Mingfeng Huang (1326141)
Kuo Song (1649239)
Hongda Wang (33141)
Yongqiang Dong (1413715)
Chaoqun Jiang (10166976)
Chenxing Zhang (7473119)
Songwei Jia (7473122)

August 2021

For each metric (i.e. precision, NMI, ARI, and F-measure) and each integration method, each data poi...

Investigation of the performance of some clustering algorithms

Tin Zar Kyaw.

January 2005

Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algo...

Comparison of different normalization methods in term of clustering accuracy in percentage.

Haixuan Yang (147680)
Cathal Seoighe (2731)

October 2016

Reported is the mean of clustering accuracies from 100 runs of Basic NMF together with the standa...

Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets

Juan Carlos Perafan-Lopez
Valeria Lucía Ferrer-Gregory
César Nieto-Londoño
Julián Sierra-Pérez

June 2022

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for ...

Average clustering coefficient for varying N and MTE = 10×N.

Christine Largeron (727149)
Pierre-Nicolas Mougel (727150)
Reihaneh Rabbany (727151)
Osmar R. Zaïane (727152)

April 2015

Average clustering coefficient for varying N and MTE = 10×N.</p

Summary table for the performance of clustering algorithms in datasets DB2C2F and DB10C2F.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

ARIdef represents the average accuracy obtained when considering the default parameters of the algor...

Summary table for the performance of clustering algorithms in datasets DB2C10F and DB10C10F.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

ARIdef represents the average accuracy obtained when considering the default parameters of the algor...

Average performance of the seven considered clustering algorithms according to the number of features in the dataset.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

All artificial datasets were used for evaluation. The averages were calculated separately for datase...

Average performance of the seven considered clustering algorithms according to the number of objects per class in the dataset.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

All artificial datasets were used for evaluation. The averages were calculated separately for datase...

Performance of clustering algorithms on real-world data.

Esha Datta (16806608)
Aditya Ballal (16806611)
Javier E. López (4543504)
Leighton T. Izu (15431237)

August 2023

Shown are the NMI score and number of clusters (m′) predicted by MapperPlus, affinity propagation, D...

Performance of the algorithm for the cluster assignment.

Kai Yu (50223)
Sholom Wacholder (50226)
William Wheeler (186671)
Zhaoming Wang (50224)
Neil Caporaso (186673)
Maria Teresa Landi (89281)
Faming Liang (186676)

January 2012

The accuracy summary for the cluster assignment is based on 50 simulated datasets under each mode...

Performance of the algorithms when changing the expected number of clusters K in the dataset.

Mayra Z. Rodriguez (6208337)
Cesar H. Comin (3724186)
Dalcimar Casanova (555517)
Odemir M. Bruno (4993505)
Diego R. Amancio (429722)
Luciano da F. Costa (429724)
Francisco A. Rodrigues (231204)

January 2019

The upper plots correspond to the ARI and Jaccard indices averaged for all datasets containing 10 cl...

Clustering Algorithms

Franěk, Dominik

January 2008

This work is an overview of some of the most frequently used algorithms for cluster analysis and som...

Performance for all classification algorithms over all peak picking and peak clustering algorithms and all replications for each dataset.

Salome Horsch (4436698)
Dominik Kopczynski (4436695)
Elias Kuthe (4436701)
Jörg Ingo Baumbach (671902)
Sven Rahmann (2715)
Jörg Rahnenführer (3861)

September 2017

Performance for all classification algorithms over all peak picking and peak clustering algorithm...

Average Adjusted Rand index to compare performances of clustering algorithms: k-means++, Qcut, kNN-Spectral and DBHT for the benchmark data sets collected by de Souto et al[40] (k++ indicates k-means++).

Won-Min Song (178326)
T. Di Matteo (178330)
Tomaso Aste (178337)

March 2012

The relatively high performing “Parameter given” results refer to cases when the true number of c...

Clustering-based performance of Dataset group #3 Gold Standard Datasets.

Ran Duan (821258)
Lin Gao (344965)
Yong Gao (29929)
Yuxuan Hu (398099)
Han Xu (68252)
Mingfeng Huang (1326141)
Kuo Song (1649239)
Hongda Wang (33141)
Yongqiang Dong (1413715)
Chaoqun Jiang (10166976)
Chenxing Zhang (7473119)
Songwei Jia (7473122)

August 2021

For each metric (i.e. precision, NMI, ARI, and F-measure) and each integration method, each data poi...

Investigation of the performance of some clustering algorithms

Tin Zar Kyaw.

January 2005

Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algo...

Comparison of different normalization methods in term of clustering accuracy in percentage.

Haixuan Yang (147680)
Cathal Seoighe (2731)

October 2016

Reported is the mean of clustering accuracies from 100 runs of Basic NMF together with the standa...

Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets

Juan Carlos Perafan-Lopez
Valeria Lucía Ferrer-Gregory
César Nieto-Londoño
Julián Sierra-Pérez

June 2022

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for ...

Average clustering coefficient for varying N and MTE = 10×N.

Christine Largeron (727149)
Pierre-Nicolas Mougel (727150)
Reihaneh Rabbany (727151)
Osmar R. Zaïane (727152)

April 2015

Average clustering coefficient for varying N and MTE = 10×N.</p

Summary table for the performance of clustering algorithms in datasets DB2C200F and DB10C200F.

Abstract

Extracted data

Summary table for the performance of clustering algorithms in datasets DB2C200F and DB10C200F.

Abstract

Extracted data

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