{ "_id": "6a10337cacfb0bcc41c98569", "Package": "tidylearn", "Title": "A Unified Tidy Interface to R's Machine Learning Ecosystem", "Version": "0.3.1.9000", "Authors@R": "person(\"Cesaire\", \"Tobias\", email = \"cesaire@sheetsolved.com\", role = c(\"aut\", \"cre\"))", "Description": "Provides a unified tidyverse-compatible interface to R's\nmachine learning ecosystem - from data ingestion to model\npublishing. The tl_read() family reads data from files ('CSV',\n'Excel', 'Parquet', 'JSON'), databases ('SQLite', 'PostgreSQL',\n'MySQL', 'BigQuery'), and cloud sources ('S3', 'GitHub',\n'Kaggle'). The tl_model() function wraps established\nimplementations from 'glmnet', 'randomForest', 'xgboost',\n'e1071', 'rpart', 'gbm', 'nnet', 'cluster', 'dbscan', and\nothers with consistent function signatures and tidy tibble\noutput. Results flow into unified 'ggplot2'-based visualization\nand optional formatted 'gt' tables via the tl_table() family.\nThe underlying algorithms are unchanged; 'tidylearn' simply\nmakes them easier to use together. Access raw model objects via\nthe $fit slot for package-specific functionality. Methods\ninclude random forests Breiman (2001)\n, LASSO regression Tibshirani\n(1996) , elastic net\nZou and Hastie (2005) ,\nsupport vector machines Cortes and Vapnik (1995)\n, and gradient boosting Friedman (2001)\n.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "URL": "https://github.com/ces0491/tidylearn", "BugReports": "https://github.com/ces0491/tidylearn/issues", "VignetteBuilder": "knitr", "Collate": "'utils.R' 'read.R' 'read-backends.R' 'core.R'\n'preprocessing.R' 'supervised-classification.R'\n'supervised-regression.R' 'supervised-regularization.R'\n'supervised-trees.R' 'supervised-svm.R'\n'supervised-neural-networks.R' 'supervised-deep-learning.R'\n'supervised-xgboost.R' 'unsupervised-distance.R'\n'unsupervised-pca.R' 'unsupervised-mds.R'\n'unsupervised-clustering.R' 'unsupervised-hclust.R'\n'unsupervised-dbscan.R' 'unsupervised-market-basket.R'\n'unsupervised-validation.R' 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