daltoolbox

DAL Toolbox

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As research experiments grow in scale and complexity, data analytics demands tools that go beyond isolated functions. DAL Toolbox is a framework designed to meet these modern challenges by organizing a comprehensive set of data analytics capabilities into an integrated workflow environment. Inspired by the Experiment Line model <doi:10.1007/978-3-642-02279-1_20>, it supports essential tasks such as data preprocessing, classification, regression, clustering, and time series prediction. With a unified data model, consistent method API, and support for hyperparameter tuning, DAL Toolbox enables the seamless construction and execution of end-to-end analytics pipelines. It also offers easy integration with existing libraries and languages, promoting usability, extensibility, and reproducibility in data science.


Examples

Graphics: https://github.com/cefet-rj-dal/daltoolbox/tree/main/graphics/

Transformation: https://github.com/cefet-rj-dal/daltoolbox/tree/main/transf/

Classification: https://github.com/cefet-rj-dal/daltoolbox/tree/main/classification/

Clustering: https://github.com/cefet-rj-dal/daltoolbox/tree/main/clustering/

Regression: https://github.com/cefet-rj-dal/daltoolbox/tree/main/regression/

The examples are organized according to general (data preprocessing), clustering, classification, regression, and time series functions.


Installation

The latest version of DAL Toolbox at CRAN is available at: https://CRAN.R-project.org/package=daltoolbox

You can install the stable version of DAL Toolbox from CRAN with:

install.packages("daltoolbox")

You can install the development version of DAL Toolbox from GitHub https://github.com/cefet-rj-dal/daltoolbox with:

library(devtools)
devtools::install_github("cefet-rj-dal/daltoolbox", force=TRUE, dependencies=FALSE, upgrade="never")

Bugs and new features request

https://github.com/cefet-rj-dal/daltoolbox/issues