Package: ClassificationEnsembles 1.1.0

ClassificationEnsembles: Automated Multi-Class Stacking Ensembles and Predictive Diagnostics

Automated multi-class classification ensemble pipeline executing concurrent parameter optimizations across logistic, tree, kernel, and neural configurations. Implements dynamic out-of-sample blending, automated feature reduction via iterative Variance Inflation Factors (VIF), and native S3 diagnostic dashboards.

Authors:Russ Conte [aut, cre, cph]

# Install 'ClassificationEnsembles' in R:

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

Bug tracker:https://github.com/infintecuriosity/classificationensembles/issues

Datasets:

Carseats - Carseats data
Cleveland_heart - Cleveland Heart
Dry_Beans - Dry Beans
Maternal_Health_Risk - Maternal Health Risk

On CRAN:

3.60 score 2 stars 5 scripts 316 downloads 7 exports 128 dependencies

Last updated from:5810a92a55. Checks:7 WARNING, 1 ERROR, 1 OK. Indexed: yes.

Target	Result	Time
linux-devel	WARNING	187
source / vignettes	ERROR	519
linux-release	WARNING	167
macos-release	WARNING	136
macos-oldrel	WARNING	132
windows-devel	WARNING	125
windows-release	WARNING	119
windows-oldrel	WARNING	129
wasm-release	OK	121

Exports:Classification ClassificationEnsemblesConfig ClassificationEnsemblesDemo ClassificationEnsemblesFastConfig load_pipeline predict_production save_pipeline

Dependencies:abind backports base64enc boot broom bslib cachem car carData caret class cli clock codetools colorspace commonmark cowplot cpp11 data.table Deriv diagram digest doBy doParallel dplyr e1071 farver fastmap fontawesome foreach forecast Formula fracdiff fs future future.apply generics ggplot2 ggrepel globals glue gower gtable hardhat htmltools httpuv ipred isoband iterators jquerylib jsonlite KernSmooth labeling later lattice lava lifecycle listenv lme4 lmtest lubridate magrittr MASS Matrix MatrixModels memoise mgcv mime minqa ModelMetrics modelr nlme nloptr nnet numDeriv otel parallelly patchwork pbkrtest pillar pkgconfig plyr pROC prodlim progressr promises proxy purrr quantreg R6 rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack recipes reformulas reshape2 rlang rpart rstudioapi S7 sass scales shape shiny sourcetools SparseM sparsevctrs SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb urca utf8 vctrs viridisLite withr xtable zoo

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Carseats data	Carseats
Comprehensive Multi-Class Classification Ensemble Pipeline Engine	Classification
Configuration Parameters Matrix for Classification Pipeline	ClassificationEnsemblesConfig
Run Fast Validation Classification Demo Suite	ClassificationEnsemblesDemo
Fast-Execution Configuration Matrix for Classification Verification	ClassificationEnsemblesFastConfig
Cleveland Heart	Cleveland_heart
Dry Beans	Dry_Beans
Load and Decompress Package Pipeline Footprints	load_pipeline
Maternal Health Risk	Maternal_Health_Risk
Plot Classification Pipeline Diagnostics Curves Canvas	plot.classification_pipeline
Executive Production Projections and Probabilities Matrix	predict_production
Predict with Classification Pipeline Object	predict.classification_pipeline
Print Classification Pipeline Summary Report	print.classification_pipeline
Compress and Save Trained Classification Pipeline Assets	save_pipeline