Package: regressoR 3.0.2
Oldemar Rodriguez
regressoR: Regression Data Analysis System
Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
Authors:
regressoR_3.0.2.tar.gz
regressoR_3.0.2.tar.gz(r-4.5-noble)regressoR_3.0.2.tar.gz(r-4.4-noble)
regressoR_3.0.2.tgz(r-4.4-emscripten)regressoR_3.0.2.tgz(r-4.3-emscripten)
regressoR.pdf |regressoR.html✨
regressoR/json (API)
NEWS
# Install 'regressoR' in R: |
install.packages('regressoR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/promidat/predictor/issues
Last updated 1 years agofrom:2e687cea7d. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 23 2024 |
R-4.5-linux | NOTE | Oct 23 2024 |
Exports:as_string_cboosting_importance_plotcalibrate_boostingcoef_lambdadatos.disyuntivosdisp_modelsdt_plote_coeff_landae_JSe_posib_lambdaexeextract_codegeneral_indicesimportance_plot_rfnn_plotpairs_powerplot_pred_rdplot_real_predictionplot_RMSEplot_var_pred_rdrd_modelrd_predictionrd_typerl_coeffrlr_modelrlr_predictionrlr_typerun_appsummary_indices
Dependencies:adaadabagattemptbackportsbase64encbitopsbroombslibcachemcaretcaToolscellrangerclasscliclockcodetoolscolorspacecolourpickercommonmarkconfigConsRankcorrplotcountrycodecpp11crayoncrosstalkdata.tableDerivdiagramdigestdoParalleldplyrDTe1071echarts4revaluatefansifarverfastmapfontawesomeforeachfreshfsfuturefuture.applygbmgenericsggplot2glmnetglobalsgluegolemgowergplotsgtablegtoolshardhatherehighrhmshtmltoolshtmlwidgetshttpuvigraphipredisobanditeratorsjquerylibjsonliteKernSmoothkknnknitrlabelinglaterlatticelavalazyevallifecyclelistenvloadeRlubridatemagrittrMASSMatrixmemoisemgcvmimeminiUIModelMetricsmunsellneuralnetnlmennetnumDerivparallellypillarpkgconfigplsplyrprettyunitspROCprodlimprogressprogressrpromisesproxypurrrR6randomForestrappdirsRColorBrewerRcppRcppEigenreadxlrecipesrematchreshape2rglrlangrlistrmarkdownROCRrpartrpart.plotrprojrootrstudioapisassscalesshapeshinyshinyAceshinycustomloadershinydashboardshinydashboardPlusshinyjssourcetoolsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytextraineRtzdbutf8vctrsviridisLitewaiterwithrwritexlxfunxgboostXMLxtableyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
The application server-side | app_server |
as_string_c | as_string_c |
boosting_importance_plot | boosting_importance_plot |
calibrate_boosting | calibrate_boosting |
coef_lambda | coef_lambda |
Create disjunctive columns to a data.frame. | datos.disyuntivos |
disp_models | disp_models |
dt_plot | dt_plot |
e_coeff_landa | e_coeff_landa |
Eval character vectors to JS code | e_JS |
e_posib_lambda | e_posib_lambda |
exe | exe |
extract_code | extract_code |
general_indices | general_indices |
importance_plot_rf | importance_plot_rf |
nn_plot | nn_plot |
pairs_power | pairs_power |
plot_pred_rd | plot_pred_rd |
plot_real_prediction | plot_real_prediction |
plot_RMSE | plot_RMSE |
plot_var_pred_rd | plot_var_pred_rd |
rd_model | rd_model |
rd_prediction | rd_prediction |
rd_type | rd_type |
rl_coeff | rl_coeff |
rlr_model | rlr_model |
rlr_prediction | rlr_prediction |
rlr_type | rlr_type |
Run the Shiny Application | run_app |
summary_indices | summary_indices |