Package: MLmorph 0.1.1

Oskar Kosch

MLmorph: Integrating Morphological Modeling and Machine Learning for Decision Support

Integrating morphological modeling with machine learning to support structured decision-making (e.g., in management and consulting). The package enumerates a morphospace of feasible configurations and uses random forests to estimate class probabilities over that space, bridging deductive model exploration with empirical validation. It includes utilities for factorizing inputs, model training, morphospace construction, and an interactive 'shiny' app for scenario exploration.

Authors:Oskar Kosch [aut, cre, cph]

MLmorph_0.1.1.tar.gz
MLmorph_0.1.1.zip(r-4.7-any)MLmorph_0.1.1.zip(r-4.6-any)MLmorph_0.1.1.zip(r-4.5-any)
MLmorph_0.1.1.tgz(r-4.6-any)MLmorph_0.1.1.tgz(r-4.5-any)
MLmorph_0.1.1.tar.gz(r-4.7-any)MLmorph_0.1.1.tar.gz(r-4.6-any)
MLmorph_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MLmorph/json (API)

# Install 'MLmorph' in R:

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

Bug tracker:https://github.com/theogrost/mlmorph/issues

On CRAN:

2.70 score 275 downloads 11 exports 117 dependencies

Last updated from:48c1bbf86e. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	132
source / vignettes	OK	215
linux-release	OK	161
macos-release	OK	130
macos-oldrel	OK	122
windows-devel	OK	74
windows-release	OK	75
windows-oldrel	OK	117
wasm-release	OK	129

Exports:create_morphospace create_rf_model factorize_binary_vector factorize_character_vector factorize_identity factorize_nicely_dataframe factorize_nicely_vector factorize_numeric_vector load_data MLmorph MLmorph_dependencies

Dependencies:askpass base64enc bslib cachem caret class cli clock codetools commonmark cpp11 crosstalk curl data.table diagram digest dplyr e1071 evaluate farver fastmap fontawesome foreach fs future future.apply generics ggplot2 globals glue gower gtable hardhat highr htmltools htmlwidgets httpuv httr ipred isoband iterators jquerylib jsonlite KernSmooth knitr labeling later lattice lava lazyeval lifecycle listenv lubridate magrittr MASS Matrix memoise mime ModelMetrics nlme nnet numDeriv openssl openxlsx otel parallelly pillar pkgconfig plotly plyr pROC prodlim progressr promises proxy purrr R6 randomForest rappdirs RColorBrewer Rcpp reactable reactR recipes reshape2 rlang rmarkdown rpart S7 sass scales shape shiny shinyFiles shinyjs sourcetools sparsevctrs SQUAREM stringi stringr survival sys tibble tidyr tidyselect timechange timeDate tinytex tzdb utf8 vctrs viridisLite withr xfun xtable yaml zip

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Create a morphospace of predictor combinations with class probabilities	create_morphospace
Create a random forest classification model	create_rf_model
Turn binary vector into a factor	factorize_binary_vector
Turn character vector into a factor	factorize_character_vector
Identity factorization for numbered strings	factorize_identity
Heuristic factorization for all columns of a data frame	factorize_nicely_dataframe
Heuristic factorization for a single vector	factorize_nicely_vector
Turn numeric vector into an ordered factor	factorize_numeric_vector
Load tabular data (xlsx, csv, or json)	load_data
Launch the MLmorph shiny app	MLmorph