Package: blockcluster 4.5.5
blockcluster: Co-Clustering Package for Binary, Categorical, Contingency and Continuous Data-Sets
Simultaneous clustering of rows and columns, usually designated by biclustering, co-clustering or block clustering, is an important technique in two way data analysis. It consists of estimating a mixture model which takes into account the block clustering problem on both the individual and variables sets. The 'blockcluster' package provides a bridge between the C++ core library build on top of the 'STK++' library, and the R statistical computing environment. This package allows to co-cluster binary <doi:10.1016/j.csda.2007.09.007>, contingency <doi:10.1080/03610920903140197>, continuous <doi:10.1007/s11634-013-0161-3> and categorical data-sets <doi:10.1007/s11222-014-9472-2>. It also provides utility functions to visualize the results. This package may be useful for various applications in fields of Data mining, Information retrieval, Biology, computer vision and many more. More information about the project and comprehensive tutorial can be found on the link mentioned in URL.
Authors:
blockcluster_4.5.5.tar.gz
blockcluster_4.5.5.tar.gz(r-4.5-noble)blockcluster_4.5.5.tar.gz(r-4.4-noble)
blockcluster_4.5.5.tgz(r-4.4-emscripten)blockcluster_4.5.5.tgz(r-4.3-emscripten)
blockcluster.pdf |blockcluster.html✨
blockcluster/json (API)
NEWS
# Install 'blockcluster' in R: |
install.packages('blockcluster', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- binarydata - Simulated Binary Data-set
- categoricaldata - Simulated categorical Data-set
- contingencydatalist - Simulated Contingency Data-set
- contingencydataunknown - Simulated Contingency Data-set
- gaussiandata - Simulated Gaussian Data-set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:240b062c1c. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 20 2024 |
R-4.5-linux-x86_64 | OK | Nov 20 2024 |
Exports:coclustercoclusterBinarycoclusterCategoricalcoclusterContingencycoclusterContinuouscoclusterStrategyplotsummary
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Getter method for blockcluster output | [ [,BinaryOptions-method [,CategoricalOptions-method [,ContingencyOptions-method [,ContinuousOptions-method [,strategy-method |
Simulated Binary Data-set | binarydata |
Binary input/output options | BinaryOptions-class |
Co-Clustering Package | blockcluster |
Simulated categorical Data-set | categoricaldata |
Categorical input/output options | CategoricalOptions-class |
Co-Clustering function. | cocluster |
Co-Clustering function for Binary data. | coclusterBinary |
Co-Clustering function for categorical data-sets. | coclusterCategorical |
Co-Clustering function. | coclusterContingency |
Co-Clustering function. | coclusterContinuous |
Strategy function | coclusterStrategy strategy-class |
Common Input/Output options. | CommonOptions-class |
Simulated Contingency Data-set | contingencydatalist |
Simulated Contingency Data-set | contingencydataunknown |
Contingency input/output options | ContingencyOptions-class |
Continuous input/output options | ContinuousOptions-class |
Simulated Gaussian Data-set | gaussiandata |
Plot function. | plot plot,BinaryOptions-method plot,CategoricalOptions-method plot,ContingencyOptions-method plot,ContinuousOptions-method |
Summary function. | summary summary,BinaryOptions-method summary,CategoricalOptions-method summary,ContingencyOptions-method summary,ContinuousOptions-method summary,strategy-method |
An EM strategy to obtain a good optimum. | XEMStrategy |