Package: fastml 0.4.0

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_0.4.0.tar.gz
fastml_0.4.0.tar.gz(r-4.5-noble)fastml_0.4.0.tar.gz(r-4.4-noble)
fastml_0.4.0.tgz(r-4.4-emscripten)fastml_0.4.0.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'))

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

2.30 score 2 scripts 634 downloads 8 exports 221 dependencies

Last updated 7 days agofrom:e8e1ef4421. Checks:2 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Jan 08 2025
R-4.5-linux	OK	Jan 08 2025

Exports:evaluate_models fastexplain fastexplore fastml load_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 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 globals glue gower GPfit gridExtra gsignal gtable hardhat highr hms htmltools htmlwidgets httpuv httr iBreakDown igraph ingredients inum ipred isoband iterators janitor 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 microbenchmark mime minqa mixOmics modelenv modelr moments munsell mvtnorm naniar nlme nloptr nnet norm numDeriv openssl parallelly parsnip partykit patchwork pbkrtest pillar pkgconfig plotly plsmod plyr polynom pracma prettyunits probably pROC prodlim progress progressr promises proxy purrr quantreg R6 ranger rappdirs rARPACK RColorBrewer Rcpp RcppEigen readr recipes repr reshape2 rgl rlang rmarkdown robustbase rpart rsample RSpectra rstatix rstudioapi sass scales sfd shape skimr slider snakecase snow sp SparseM SQUAREM stringi stringr survival svglite sys systemfonts tibble tidyr tidyselect timechange timeDate tinytex tune tzdb UpSetR utf8 vcd vctrs VIM viridis viridisLite visdat vroom warp withr workflows xfun xml2 yaml yardstick zoo

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Readme and manuals

Help Manual

Help page	Topics
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
Load Model Function	load_model
Plot Function for fastml_model	plot.fastml_model
Predict Function for fastml_model	predict.fastml_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 0.4.0

fastml: Fast Machine Learning Model Training and Evaluation

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)