Other packages > Find by keyword >

FisherEM  

The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data
View on CRAN: Click here


Download and install FisherEM package within the R console
Install from CRAN:
install.packages("FisherEM")

Install from Github:
library("remotes")
install_github("cran/FisherEM")

Install by package version:
library("remotes")
install_version("FisherEM", "1.6")



Attach the package and use:
library("FisherEM")
Maintained by
Charles Bouveyron
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-05-11
Latest Update: 2020-09-28
Description:
The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) , is an efficient method for the clustering of high-dimensional data. FisherEM models and clusters the data in a discriminative and low-dimensional latent subspace. It also provides a low-dimensional representation of the clustered data. A sparse version of Fisher-EM algorithm is also provided.
How to cite:
Charles Bouveyron (2011). FisherEM: The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data. R package version 1.6, https://cran.r-project.org/web/packages/FisherEM. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0 (2011-05-11 17:03), 1.1.2 (2011-05-29 20:39), 1.2 (2012-07-13 05:08), 1.3.1 (2013-02-20 08:04), 1.3.2 (2013-02-21 17:36), 1.3 (2013-02-13 07:57), 1.4 (2013-06-28 18:44), 1.5.1 (2018-10-11 12:10), 1.5.2 (2020-07-22 10:42), 1.5 (2018-10-09 17:20)
Other packages that cited FisherEM R package
View FisherEM citation profile
Other R packages that FisherEM depends, imports, suggests or enhances
Complete documentation for FisherEM
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
Rfast2  
A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
LOGANTree  
Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency  
Maintainer: Qi Qin (view profile)
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA