Package: symbolicr 1.0.0.9000

Danilo Tomasoni

symbolicr: Symbolic Regression Framework

Find non-linear formulas that fits your input data. You can systematically explore and memorize the possible formulas and it's cross-validation performance, in an incremental fashion. Three main interoperable search functions are available: 1) random.search() performs a random exploration, 2) genetic.search() employs a genetic optimization algorithm, 3) comb.search() combines best results of the first two. For more details see Tomasoni et al. (2026) <doi:10.1208/s12248-026-01232-z>.

Authors:Danilo Tomasoni [aut, cre], Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology COSBI [cph, fnd]

symbolicr_1.0.0.9000.tar.gz
symbolicr_1.0.0.9000.zip(r-4.7-any)symbolicr_1.0.0.9000.zip(r-4.6-any)symbolicr_1.0.0.9000.zip(r-4.5-any)
symbolicr_1.0.0.9000.tgz(r-4.6-any)symbolicr_1.0.0.9000.tgz(r-4.5-any)
symbolicr_1.0.0.9000.tar.gz(r-4.7-any)symbolicr_1.0.0.9000.tar.gz(r-4.6-any)
symbolicr_1.0.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
symbolicr/json (API)

# Install 'symbolicr' in R:
install.packages('symbolicr', repos = c('https://cosbi-research.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cosbi-research/symbolicr/issues

On CRAN:

Conda:

5.02 score 1 stars 5 scripts 359 downloads 17 exports 20 dependencies

Last updated from:1cd31e61d2. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK128
source / vignettesOK166
linux-releaseOK116
macos-releaseOK171
macos-oldrelOK179
windows-develOK91
windows-releaseOK72
windows-oldrelOK92
wasm-releaseOK96

Exports:analyze.variablescomb.searchcross.validateempty.sampleexaustive.searchgenetic.searchmonitor.formula.funnormalizeparse.varspe.r.squared.formula.len.fitnesspred.vs.obsrandom.searchregressorsregressors.namesserialize.varstest.formulatransformations.names

Dependencies:clicodetoolscpp11crayondata.tableforeachGAgluegmpgtoolsiteratorslifecyclemagrittrRcppRcppAlgosRcppArmadillorlangstringistringrvctrs

formula-analysis
Simple one-formula analysis | Set-up the data and load the shared results | Differential analysis, preparation | Differential analysis
Rendered fromformula-analysis.Rmdusingknitr::rmarkdown

Last update: 2024-07-22
Started: 2024-07-22

get-started
Load the library and set-up the data | Define hyper-parameters | Define rData file for checkpoint save | Define non-linear transformations | Start symbolic regression
Rendered fromget-started.Rmdusingknitr::rmarkdown

Last update: 2024-07-22
Started: 2024-06-25

join-results
Collecting results from parallel independent tests | Define base.filepaths | Check exploration space percentage | Load in one-shot all the independent results | Differential analysis (preparation) | Update shared results
Rendered fromjoin-results.Rmdusingknitr::rmarkdown

Last update: 2024-07-22
Started: 2024-07-22