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# CITATION.cff file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "PsyML" in publications use:'
type: software
license: MIT
title: 'PsyML: Machine Learning Workflows for Supervised, Unsupervised, and Causal
  Analysis'
version: 2.4.2
abstract: Provides single-function pipelines for applied machine learning with tabular
  data, as commonly found in psychological, behavioral, and health research. The supervised
  pipeline, supervised_ml(), performs exploratory checks, preprocessing, training
  of several models with cross-validation, hyperparameter tuning, test-set evaluation,
  threshold optimization, calibration, fairness analysis, decision curve analysis,
  and model interpretation with permutation importance and Shapley values. The unsupervised
  pipeline, unsupervised_ml(), covers k-means, hierarchical, DBSCAN, Gaussian mixture,
  and latent class clustering with selection of the number of clusters, dimensionality
  reduction (PCA, t-SNE, UMAP), and anomaly detection (isolation forest, local outlier
  factor, Mahalanobis distance). The causal pipeline, causal_ml(), estimates treatment
  effects with propensity scores, meta-learners, double machine learning, causal forests,
  and targeted maximum likelihood estimation. Also includes learning-curve based sample
  size estimation, block and diversity-based data splitting, and export of results
  to text and JSON.
authors:
- family-names: Ventura-Leon
  given-names: Jose
  email: jventuraleon@gmail.com
  orcid: https://orcid.org/0000-0003-2996-4244
repository: https://cran.r-universe.dev
repository-code: https://github.com/jventural/PsyML
commit: 1ec404577e481f4f2f95e817874a7263b027771f
url: https://github.com/jventural/PsyML
date-released: '2026-10-25'
contact:
- family-names: Ventura-Leon
  given-names: Jose
  email: jventuraleon@gmail.com
  orcid: https://orcid.org/0000-0003-2996-4244