Package: fastml 0.5.0

Selcuk Korkmaz

fastml: Fast Machine Learning Model Training and Evaluation

Streamlines the training, evaluation, and comparison of multiple machine learning models with minimal code by providing comprehensive data preprocessing and support for a wide range of algorithms with hyperparameter tuning. It offers performance metrics and visualization tools to facilitate efficient and effective machine learning workflows.

Authors:Selcuk Korkmaz [aut, cre], Dincer Goksuluk [aut], Eda Karaismailoglu [aut]

fastml_0.5.0.tar.gz
fastml_0.5.0.tar.gz(r-4.5-noble)fastml_0.5.0.tar.gz(r-4.4-noble)
fastml_0.5.0.tgz(r-4.4-emscripten)fastml_0.5.0.tgz(r-4.3-emscripten)
fastml.pdf |fastml.html✨
fastml/json (API)

# Install 'fastml' in R:

install.packages('fastml', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.76 score 23k downloads 19 exports 238 dependencies

Last updated 2 days agofrom:5325fbdf0d. Checks:3 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 07 2025
R-4.5-linux	OK	Mar 07 2025
R-4.4-linux	OK	Mar 07 2025

Exports:availableMethods evaluate_models fastexplain fastexplore fastml flatten_and_rename_models get_best_model_idx get_best_model_names get_best_workflows get_default_engine get_default_params get_default_tune_params get_engine_names get_model_engine_names load_model process_model sanitize save_model train_models

Dependencies:abind askpass backports baguette base64enc BH BiocParallel bit bit64 bonsai boot broom bslib butcher C50 cachem car carData class cli clipr clock codetools colorspace corpcor corrplot cowplot cpp11 crayon crosstalk Cubist curl DALEX data.table dbscan DEoptimR Deriv diagram dials DiceDesign digest discrim doBy doFuture doRNG dplyr DT e1071 ellipse evaluate fansi farver fastmap finetune fontawesome forcats foreach formatR Formula fs furrr futile.logger futile.options future future.apply generics GGally ggplot2 ggpubr ggrepel ggsci ggsignif ggstats glmnet globals glue gower GPfit gridExtra gsignal gtable hardhat haven highr hms htmltools htmlwidgets httpuv httr iBreakDown igraph ingredients inum ipred isoband iterators itertools janitor jomo jquerylib jsonlite kableExtra KernSmooth knitr labeling laeken lambda.r later lattice lava lazyeval lhs libcoin lifecycle listenv lme4 lmtest lobstr lubridate magrittr MASS Matrix MatrixModels matrixStats memoise mgcv mice microbenchmark mime minqa missForest mitml mixOmics modelenv modelr moments munsell mvtnorm naniar nlme nloptr nnet norm numDeriv openssl ordinal pan parallelly parsnip partykit patchwork pbkrtest pillar pkgconfig plotly plsmod plyr polynom pracma prettyunits probably pROC prodlim progress progressr promises proxy purrr quantreg R6 randomForest ranger rappdirs rARPACK rbibutils RColorBrewer Rcpp RcppEigen Rdpack readr recipes reformulas repr reshape2 rgl rlang rmarkdown rngtools robustbase rpart rsample RSpectra rstatix rstudioapi sass scales sfd shape skimr slider snakecase snow sp SparseM sparsevctrs SQUAREM stringi stringr survival svglite sys systemfonts tibble tidyr tidyselect timechange timeDate tinytex tune tzdb ucminf UpSetR utf8 vcd vctrs VIM viridis viridisLite visdat vroom warp withr workflows xfun xml2 yaml yardstick zoo

Citation

Readme and manuals

Help Manual

Help page	Topics
Get Available Methods	availableMethods
Evaluate Models Function	evaluate_models
FastExplain the fastml_model (DALEX + SHAP + Permutation-based VI)	fastexplain
Explore and Summarize a Dataset Quickly	fastexplore
Fast Machine Learning Function	fastml
Flatten and Rename Models	flatten_and_rename_models
Get Best Model Indices by Metric and Group	get_best_model_idx
Get Best Model Names	get_best_model_names
Get Best Workflows	get_best_workflows
Get Default Engine	get_default_engine
Get Default Parameters for an Algorithm	get_default_params
Get Default Tuning Parameters	get_default_tune_params
Get Engine Names from Model Workflows	get_engine_names
Get Model Engine Names	get_model_engine_names
Load Model Function	load_model
Plot Function for fastml_model	plot.fastml_model
Predict Function for fastml_model	predict.fastml_model
Process Model and Compute Performance Metrics	process_model
Clean Column Names or Character Vectors by Removing Special Characters	sanitize
Save Model Function	save_model
Summary Function for fastml_model (Using yardstick for ROC Curves)	summary.fastml_model
Train Specified Machine Learning Algorithms on the Training Data	train_models

Package: fastml 0.5.0

fastml: Fast Machine Learning Model Training and Evaluation

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)