Feature selection, Random Forest, and SEM workflow for simulated stand dataset
<p dir="ltr">This dataset and R script provide the workflow for analyzing stand structure and productivity of Chinese fir (<i>Cunninghamia lanceolata</i>) stands using simulated data. The dataset includes key stand, site, and climate variables. The R script demonstrates t...
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2025
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| _version_ | 1852015454863753216 |
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| author | yang guo (22176595) |
| author_facet | yang guo (22176595) |
| author_role | author |
| dc.creator.none.fl_str_mv | yang guo (22176595) |
| dc.date.none.fl_str_mv | 2025-10-28T10:44:18Z |
| dc.identifier.none.fl_str_mv | 10.6084/m9.figshare.30189961.v1 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Feature_selection_Random_Forest_and_SEM_workflow_for_simulated_stand_dataset/30189961 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Forestry management and environment Random Forest, SEM, Feature Selection |
| dc.title.none.fl_str_mv | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p dir="ltr">This dataset and R script provide the workflow for analyzing stand structure and productivity of Chinese fir (<i>Cunninghamia lanceolata</i>) stands using simulated data. The dataset includes key stand, site, and climate variables. The R script demonstrates the following steps:</p><ol><li>Feature selection with the Boruta algorithm</li><li>Random Forest modeling with cross-validation and stepwise variable elimination</li><li>Multicollinearity diagnostics using VIF</li><li>Structural Equation Modeling (SEM) and effect decomposition with <code>piecewiseSEM</code> and <code>semEff</code><b>Notes</b></li><li>The dataset is simulated for reproducibility and does not include raw inventory data.</li><li>Users may adapt the script to their own datasets for similar analyses in forestry and ecology.</li></ol><p></p> |
| eu_rights_str_mv | openAccess |
| id | Manara_ebd2d4084ddf05ab2ac83addde375d38 |
| identifier_str_mv | 10.6084/m9.figshare.30189961.v1 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30189961 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Feature selection, Random Forest, and SEM workflow for simulated stand datasetyang guo (22176595)Forestry management and environmentRandom Forest, SEM, Feature Selection<p dir="ltr">This dataset and R script provide the workflow for analyzing stand structure and productivity of Chinese fir (<i>Cunninghamia lanceolata</i>) stands using simulated data. The dataset includes key stand, site, and climate variables. The R script demonstrates the following steps:</p><ol><li>Feature selection with the Boruta algorithm</li><li>Random Forest modeling with cross-validation and stepwise variable elimination</li><li>Multicollinearity diagnostics using VIF</li><li>Structural Equation Modeling (SEM) and effect decomposition with <code>piecewiseSEM</code> and <code>semEff</code><b>Notes</b></li><li>The dataset is simulated for reproducibility and does not include raw inventory data.</li><li>Users may adapt the script to their own datasets for similar analyses in forestry and ecology.</li></ol><p></p>2025-10-28T10:44:18ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.6084/m9.figshare.30189961.v1https://figshare.com/articles/dataset/Feature_selection_Random_Forest_and_SEM_workflow_for_simulated_stand_dataset/30189961CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/301899612025-10-28T10:44:18Z |
| spellingShingle | Feature selection, Random Forest, and SEM workflow for simulated stand dataset yang guo (22176595) Forestry management and environment Random Forest, SEM, Feature Selection |
| status_str | publishedVersion |
| title | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| title_full | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| title_fullStr | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| title_full_unstemmed | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| title_short | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| title_sort | Feature selection, Random Forest, and SEM workflow for simulated stand dataset |
| topic | Forestry management and environment Random Forest, SEM, Feature Selection |