Last updated: 2025-07-09

Checks: 6 1

Knit directory: Machine-learning-e-redes-neurais-artificiais-no-melhoramento-genetico-do-cafeeiro/

This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: uncommitted changes

The R Markdown file has unstaged changes. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20250709)

The command set.seed(20250709) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: c690214

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version c690214. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: 


Ignored files:
    Ignored:    .Rproj.user/

Unstaged changes:
    Modified:   analysis/about.Rmd
    Modified:   analysis/index.Rmd
    Modified:   analysis/license.Rmd

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/license.Rmd) and HTML (docs/license.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd 2f5fdb9 WevertonGomesCosta 2025-07-09 add license
html 2f5fdb9 WevertonGomesCosta 2025-07-09 add license
Rmd be23fb6 WevertonGomesCosta 2025-07-09 Start workflowr project.

Este material foi produzido por Costa, W. G., está licenciado sob a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Isso significa que você é livre para:

Desde que você siga os termos da licença:

Para mais informações, consulte a licença completa em:
https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.pt

This material was produced by Costa, W. G., is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This means you are free to:

As long as you follow the license terms:

For more information, see the full license at:
https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode


sessionInfo()
R version 4.4.3 (2025-02-28 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=Portuguese_Brazil.utf8  LC_CTYPE=Portuguese_Brazil.utf8   
[3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C                      
[5] LC_TIME=Portuguese_Brazil.utf8    

time zone: America/Sao_Paulo
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] vctrs_0.6.5       cli_3.6.5         knitr_1.50        rlang_1.1.6      
 [5] xfun_0.52         stringi_1.8.7     promises_1.3.3    jsonlite_2.0.0   
 [9] workflowr_1.7.1   glue_1.8.0        rprojroot_2.0.4   git2r_0.36.2     
[13] htmltools_0.5.8.1 httpuv_1.6.16     sass_0.4.10       rmarkdown_2.29   
[17] evaluate_1.0.3    jquerylib_0.1.4   tibble_3.3.0      fastmap_1.2.0    
[21] yaml_2.3.10       lifecycle_1.0.4   whisker_0.4.1     stringr_1.5.1    
[25] compiler_4.4.3    fs_1.6.6          Rcpp_1.0.14       pkgconfig_2.0.3  
[29] rstudioapi_0.17.1 later_1.4.2       digest_0.6.37     R6_2.6.1         
[33] pillar_1.10.2     magrittr_2.0.3    bslib_0.9.0       tools_4.4.3      
[37] cachem_1.1.0

  1. Weverton Gomes da Costa, Pós-Doutorando, Departamento de Estatística - Universidade Federal de Viçosa, ↩︎