Search alternatives:
"different clustering algorithm" » "different countries algorithm" (Expand Search), "different criteria algorithm" (Expand Search)
"light processing algorithm" » "signal processing algorithm" (Expand Search), "post processing algorithm" (Expand Search), "time processing algorithm" (Expand Search)
Showing 1 - 20 results of 38 for search '(("different clustering algorithm") OR ("light processing algorithm"))', query time: 1.04s Refine Results
  1. 1
    AMI, ARI and NMI accuracy on two real-world networks.

    AMI, ARI and NMI accuracy on two real-world networks. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  2. 2
    Experiment 2: Evaluating modularity-based consensus clustering pipelines on synthetic networks based on clustered real-world networks.

    Experiment 2: Evaluating modularity-based consensus clustering pipelines on synthetic networks based on clustered real-world networks. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  3. 3
    Experiment 4: Accuracy of modularity-based consensus clustering methods on ring-of-cliques networks of varying sizes.

    Experiment 4: Accuracy of modularity-based consensus clustering methods on ring-of-cliques networks of varying sizes. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  4. 4
    Experiment 4: Evaluating modularity-based clustering methods on tree-of-cliques networks.

    Experiment 4: Evaluating modularity-based clustering methods on tree-of-cliques networks. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  5. 5
    List of abbreviations.

    List of abbreviations. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  6. 6
    Evaluating stability across multiple stochastic runs on the algorithm design datasets.

    Evaluating stability across multiple stochastic runs on the algorithm design datasets. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  7. 7
    Experiment 3: Comparison of FastEnsemble(Leiden-CPM) and Leiden-CPM on synthetic networks based on clustered real-world networks.

    Experiment 3: Comparison of FastEnsemble(Leiden-CPM) and Leiden-CPM on synthetic networks based on clustered real-world networks. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  8. 8
    Empirical statistics of the networks used in this study.

    Empirical statistics of the networks used in this study. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  9. 9
    Experiment 1a: Setting the default value for t in FastEnsemble.

    Experiment 1a: Setting the default value for t in FastEnsemble. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  10. 10
    Experiment 5: Clustering networks that are only partially clusterable.

    Experiment 5: Clustering networks that are only partially clusterable. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  11. 11
    Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter.

    Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  12. 12
    Experiment 4: Evaluating CPM-based clustering methods on ring-of-cliques networks.

    Experiment 4: Evaluating CPM-based clustering methods on ring-of-cliques networks. by Yasamin Tabatabaee (18095491)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  13. 13
    Clusterings’ visualization obtained by t-SNE from the <i>D</i><sub>4</sub> dataset, considering the best pair MPO_ROCK (descriptor_clustering algorithm), and according to the CALINSKI metric.

    Clusterings’ visualization obtained by t-SNE from the <i>D</i><sub>4</sub> dataset, considering the best pair MPO_ROCK (descriptor_clustering algorithm), and according to the CALIN... by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  14. 14
    Results obtained by each descriptor and clustering method ROCK, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>4</sub>.

    Results obtained by each descriptor and clustering method ROCK, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>4</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  15. 15
    Classes’ descriptions and samples’ distribution for each class of dataset <i>D</i><sub>4</sub>.

    Classes’ descriptions and samples’ distribution for each class of dataset <i>D</i><sub>4</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  16. 16
    Clusterings’ visualization obtained by PCA from the <i>D</i><sub>4</sub> dataset, considering the best pair RCS_ROCK (descriptor_clustering algorithm), and according to the accuracy metric.

    Clusterings’ visualization obtained by PCA from the <i>D</i><sub>4</sub> dataset, considering the best pair RCS_ROCK (descriptor_clustering algorithm), and according to the accurac... by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  17. 17
    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>3</sub>.

    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>3</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  18. 18
    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>1</sub>.

    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>1</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  19. 19
    Results obtained by each descriptor and clustering method CURE, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>2</sub>.

    Results obtained by each descriptor and clustering method CURE, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>2</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:
  20. 20
    Clusterings’ visualization obtained by PCA from the <i>D</i><sub>4</sub> dataset, considering the best pair TAMURA_ROCK (descriptor_clustering algorithm), and according to the DAVIES metric.

    Clusterings’ visualization obtained by PCA from the <i>D</i><sub>4</sub> dataset, considering the best pair TAMURA_ROCK (descriptor_clustering algorithm), and according to the DAVI... by Eduardo R. de Oliveira (16883983)

    Published 2023
    Subjects:
    Save to List
    Saved in:

Search Tools: