This repository showcases the use of the FRESA.CAD::ILAA(), FRESA.CAD::IDeA() and the FRESA.CAD::getLatentCoefficients() for the discovery of latent variables from tabular data-sets.
Examples of usage and applications of the FRESA.CAD::ILAA() and the associated exploratory residualization matrix (ERT).
This repository also holds the Source code of the Shiny App: ERT Calculator the source code is at the ILAA folder.
The repository folder structure is:
| Folder Name | Contents |
|---|---|
| Data | Data sets used in the examples of this repository: Data |
| ILAA | Shiny App code |
| Main | The ILAA Tutorial Code |
| RMD | The RMD scripts used for the validation and showcasing the ILAA method |
ILAA is part of the FRESA.CAD package. To use ILAA first install FRESA.CAD You can install the official release of the package from CRAN using:
install.packages("FRESA.CAD")To install the development version from GitHub, use:
# Install 'devtools' package if you haven't already
install.packages("devtools")
# Install the package from GitHub
devtools::install_github("https://github.com/joseTamezPena/FRESA.CAD")After installation you can test ILAA on the iris data set.
library("FRESA.CAD")
# The IRIS dataset
data('iris')
##FCA Decorrelation at 0.25 threshold, pearson and fast estimation
irisDecor <- ILAA(iris,thr=0.25)
# Print the latent variables
print(getLatentCoefficients(irisDecor))
# Lets model setosa using logistic regression
setosaData <- iris
setosaData$setosa <- 1.0*(as.character(iris$Species)=="setosa")
setosaData$Species <- NULL
setosaILAA <- ILAA(setosaData,thr=0.25)
modelSetosa <- glm(setosa~.,setosaILAA,family="binomial")
#The model cofficients in the ERT space
print(modelSetosa$coefficients)
#Get the observed Coefficients
observedCoef <- getObservedCoef(setosaILAA,modelSetosa)
#The model cofficients in the Observed space
print(observedCoef)
You can test ILAA using the ERT calculator at: https://josetamezpena.shinyapps.io/ILAA/
The app will compute the ERT transformation using the user-provided data set.
Also you can look at the output of the ILAA tutorial at: https://rpubs.com/J_Tamez/ILAA_Tutorial
Contributions are welcome! If you'd like to contribute to this project, please follow these guidelines:
- Fork the repository.
- Create a new branch:
git checkout -b feature/new-feature. - Make your changes and commit them:
git commit -m 'Add new feature'. - Push to the branch:
git push origin feature/new-feature. - Submit a pull request.
This project is licensed under the LGPL Licence 3.0 see the LICENSE file for details.
Email: jose.tamezpena@tec.mx
Twitter: @tamezpena