Package: PsyML
Type: Package
Title: Machine Learning Workflows for Supervised, Unsupervised, and
        Causal Analysis
Version: 2.4.2
Date: 2026-10-25
Authors@R: c(
    person("Jose", "Ventura-Leon",
           email = "jventuraleon@gmail.com",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-2996-4244"))
    )
Description: 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.
License: MIT + file LICENSE
URL: https://github.com/jventural/PsyML
BugReports: https://github.com/jventural/PsyML/issues
Encoding: UTF-8
RoxygenNote: 7.3.2
Depends: R (>= 4.1.0)
Imports: dials, dplyr, ggplot2, grDevices, graphics, hardhat, jsonlite,
        nnet, parallel, parsnip, pROC, ranger, recipes, rlang, rsample,
        stats, tibble, tidyr, tidyselect, tune, utils, workflows,
        xgboost, yardstick
Suggests: Boruta, bslib, cluster, cobalt, commonmark, dbscan,
        doParallel, DoubleML, DT, e1071, finetune, flextable, foreach,
        ggdendro, glmnet, grf, htmltools, httr, httr2, isotree,
        kernelshap, kernlab, knitr, MatchIt, mclust, mlr3,
        mlr3learners, officer, patchwork, poLCA, readxl, reticulate,
        rmarkdown, rpart, Rtsne, shapviz, shiny, shinydashboard,
        SuperLearner, testthat (>= 3.0.0), themis, tmle, umap, VIM
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-10-26 03:23:54 UTC; PC
Author: Jose Ventura-Leon [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-2996-4244>)
Maintainer: Jose Ventura-Leon <jventuraleon@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-12 15:00:02 UTC
Built: R 4.5.2; ; 2026-11-12 16:26:05 UTC; unix
