RclusTool
RclusTool is a clustering and visualization R toolbox.
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
-
○.zenodo.json file
-
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (5.7%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
·
Repository
RclusTool is a clustering and visualization R toolbox.
Basic Info
- Host: gitlab.com
- Owner: PAHebert
- Default Branch: master
Statistics
- Stars: 0
- Forks: 0
- Open Issues: 30
- Releases: 0
Created almost 8 years ago
Metadata Files
Readme
License
Citation
README.md
Welcome to RclusTool [R package]
What is RclusTool ?
RclusTool is a Clustering and visualization toolbox.
Package content
- visualization and processing of data with different formats: profile/time series, features and images
- unsupervised clustering
- semi-supervised clustering
- supervised classification
- labeling expert interface
- constraint expert labeling (matching without specific name : points must be link or can not link)
How to use this R package
From a R console:
{r}
library(RclusTool)
RclusTool()
Contributing organizations
Development
Other contributions

Funding partners
Contact us at hebert[at]univ[-]littoral[dot]fr
Citation (CITATION)
bibentry(bibtype = "Article",
header = "This package relies on Constrained spectral embedding for K-way data clustering:",
title = "Constrained spectral embedding for K-way data clustering",
author = "Guillaume Wacquet, Emilie Poisson Caillault, Denis Hamad, Pierre-Alexandre Hebert",
journal = "Pattern Recognition Letters",
year = "2013",
volume = "34",
number = "9",
pages = "1009--1017",
url = "https://hal.archives-ouvertes.fr/hal-01536663",
pdf = "https://hal.archives-ouvertes.fr/hal-01536663/file/2013.PRL.pdf",
doi = "10.1016/j.patrec.2013.02.003",
## textVersion = paste("Guillaume Wacquet, Emilie Poisson Caillault, Denis Hamad, Pierre-Alexandre Hebert (2013).",
## "Constrained spectral embedding for K-way data clustering.",
## "Pattern Recognition Letters, 34(9), 1009-1017.",
## "URL https://doi.org/10.1016/j.patrec.2013.02.003"),
)
bibentry(bibtype = "Inbook",
title = "Semi-supervised K-Way Spectral Clustering with Determination of Number of Clusters",
author = "Guillaume Wacquet, Emilie Poisson Caillault, Pierre-Alexandre Hebert",
editor = "Madani, Kurosh and Dourado, Antonio and Rosa, Agostinho and Filipe, Joaquim",
bookTitle = "Computational Intelligence: Revised and Selected Papers of the International Joint Conference, IJCCI 2011, Paris, France, October 24-26, 2011",
chapter = "Semi-supervised K-Way Spectral Clustering with Determination of Number of Clusters",
year = "2013",
publisher = "Springer Berlin Heidelberg",
address = "Berlin, Heidelberg",
pages = "317--332",
isbn = "978-3-642-35638-4",
doi = "10.1007/978-3-642-35638-4_21"
)
Dependencies
DESCRIPTION
cran
- R >= 3.0.0 depends
- tcltk * depends
- tcltk2 * depends
- tkrplot * depends
- FactoMineR * imports
- MASS * imports
- SearchTrees * imports
- class * imports
- cluster * imports
- conclust * imports
- corrplot * imports
- e1071 * imports
- factoextra * imports
- ggplot2 * imports
- grid * imports
- jpeg * imports
- knitr * imports
- mclust * imports
- mda * imports
- mmand * imports
- nnet * imports
- png * imports
- randomForest * imports
- reshape * imports
- rlang * imports
- sp * imports
- stats * imports
- stringi * imports
- stringr * imports
- tools * imports




