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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "MLwrap" in publications use:'
type: software
license: GPL-3.0-only
title: 'MLwrap: Machine Learning Modelling for Everyone'
version: 0.3.0
doi: 10.32614/CRAN.package.MLwrap
abstract: A minimal library specifically designed to make the estimation of Machine
  Learning (ML) techniques as easy and accessible as possible, particularly within
  the framework of the Knowledge Discovery in Databases (KDD) process in data mining.
  The package provides essential tools to structure and execute each stage of a predictive
  or classification modeling workflow, aligning closely with the fundamental steps
  of the KDD methodology, from data selection and preparation, through model building
  and tuning, to the interpretation and evaluation of results using Sensitivity Analysis.
  The 'MLwrap' workflow is organized into four core steps; preprocessing(), build_model(),
  fine_tuning(), and sensitivity_analysis(). It also includes global and pairwise
  interaction analysis based on Friedman’s H-statistic to support a more detailed
  interpretation of complex feature relationships.These steps correspond, respectively,
  to data preparation and transformation, model construction, hyperparameter optimization,
  and sensitivity analysis. The user can access comprehensive model evaluation results
  including fit assessment metrics, plots, predictions, and performance diagnostics
  for ML models implemented through 'Neural Networks', 'Random Forest', 'XGBoost'
  (Extreme Gradient Boosting), and 'Support Vector Machines' (SVM) algorithms. By
  streamlining these phases, 'MLwrap' aims to simplify the implementation of ML techniques,
  allowing analysts and data scientists to focus on extracting actionable insights
  and meaningful patterns from large datasets, in line with the objectives of the
  KDD process.
authors:
- family-names: Martínez García
  given-names: Javier
  email: javier.nezcia@gmail.com
  orcid: https://orcid.org/0009-0007-7861-5274
- family-names: Sesé
  given-names: Albert
  email: albert.sese@uib.es
  orcid: https://orcid.org/0000-0003-3771-1749
repository: https://albertsesepsy.r-universe.dev
repository-code: https://github.com/AlbertSesePsy/MLwrap
commit: 2290068b4ca71dbe2eea90f464175089d89070d3
url: https://github.com/AlbertSesePsy/MLwrap
date-released: '2025-12-15'
contact:
- family-names: Sesé
  given-names: Albert
  email: albert.sese@uib.es
  orcid: https://orcid.org/0000-0003-3771-1749