Package: Evacluster 0.1.0
Evacluster: Evaluation Clustering Methods for Disease Subtypes Diagnosis
Contains a set of clustering methods and evaluation metrics to select the best number of the clusters based on clustering stability. Two references describe the methodology: Fahimeh Nezhadmoghadam, and Jose Tamez-Pena (2021)<doi:10.1016/j.compbiomed.2021.104753>, and Fahimeh Nezhadmoghadam, et al.(2021)<doi:10.2174/1567205018666210831145825>.
Authors:
Evacluster_0.1.0.tar.gz
Evacluster_0.1.0.zip(r-4.5)Evacluster_0.1.0.zip(r-4.4)Evacluster_0.1.0.zip(r-4.3)
Evacluster_0.1.0.tgz(r-4.4-any)Evacluster_0.1.0.tgz(r-4.3-any)
Evacluster_0.1.0.tar.gz(r-4.5-noble)Evacluster_0.1.0.tar.gz(r-4.4-noble)
Evacluster_0.1.0.tgz(r-4.4-emscripten)Evacluster_0.1.0.tgz(r-4.3-emscripten)
Evacluster.pdf |Evacluster.html✨
Evacluster/json (API)
| # Install 'Evacluster' in R: |
| install.packages('Evacluster', repos = c('https://fahimehnm.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:e35fbae9b4. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 16 2024 |
| R-4.5-win | NOTE | Sep 16 2024 |
| R-4.5-linux | NOTE | Sep 16 2024 |
| R-4.4-win | NOTE | Sep 16 2024 |
| R-4.4-mac | NOTE | Sep 16 2024 |
| R-4.3-win | OK | Sep 16 2024 |
| R-4.3-mac | OK | Sep 16 2024 |
Exports:clusterStabilityEMClusterFuzzyClustergetConsensusClusterhierarchicalClusterkmeansClusternmfClusterpamClusterpredict.EMClusterpredict.FuzzyClusterpredict.hierarchicalClusterpredict.kmeansClusterpredict.nmfClusterpredict.pamClusterpredict.tsneReductortsneReductor
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Evaluation Clustering Methods for Disease Subtypes Diagnosis (Evacluster) | Evacluster-package Evacluster |
| clustering stability function | clusterStability |
| Expectation Maximization Clustering | EMCluster |
| Fuzzy C-means Clustering Algorithm | FuzzyCluster |
| Consensus Clustering Results | getConsensusCluster |
| hierarchical clustering | hierarchicalCluster |
| K-means Clustering | kmeansCluster |
| Non-negative matrix factorization (NMF) | nmfCluster |
| Partitioning Around Medoids (PAM) Clustering | pamCluster |
| EMCluster prediction function | predict.EMCluster |
| FuzzyCluster prediction function | predict.FuzzyCluster |
| hierarchicalCluster prediction function | predict.hierarchicalCluster |
| kmeansCluster prediction function | predict.kmeansCluster |
| nmfCluster prediction function | predict.nmfCluster |
| pamCluster prediction function | predict.pamCluster |
| tsneReductor prediction function | predict.tsneReductor |
| t-Distributed Stochastic Neighbor Embedding (t-SNE) | tsneReductor |
