Package: trama.ml 0.5.8
trama.ml: Interpretable and Classical Machine Learning for trama
Supervised learning nodes for trama workflows, from linear baselines and interpretable CART and FIGS models to random forests, support vector machines and gradient boosted trees. Provides reproducible training and test splits, prediction, evaluation and model inspection. Learning engines are optional and loaded only for the selected model. Neural networks are deliberately outside the scope of this collection.
Authors:
trama.ml_0.5.8.tar.gz
trama.ml_0.5.8.zip(r-4.7-any)trama.ml_0.5.8.zip(r-4.6-any)trama.ml_0.5.8.zip(r-4.5-any)
trama.ml_0.5.8.tgz(r-4.6-any)trama.ml_0.5.8.tgz(r-4.5-any)
trama.ml_0.5.8.tar.gz(r-4.7-any)trama.ml_0.5.8.tar.gz(r-4.6-any)
trama.ml_0.5.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
trama.ml/json (API)
| # Install 'trama.ml' in R: |
| install.packages('trama.ml', repos = c('https://uaipedro.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/uaipedro/trama/issues
Last updated from:1bdeb4f693. Checks:7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | WARNING | 147 | ||
| source / vignettes | OK | 257 | ||
| linux-release | WARNING | 139 | ||
| macos-release | WARNING | 117 | ||
| macos-oldrel | WARNING | 115 | ||
| windows-devel | WARNING | 106 | ||
| windows-release | WARNING | 144 | ||
| windows-oldrel | WARNING | 110 | ||
| wasm-release | OK | 126 |
Exports:tr_ml_carttr_ml_exampletr_ml_figstr_ml_fittr_ml_foresttr_ml_lineartr_ml_nested_cvtr_ml_residualstr_ml_rulestr_ml_splittr_ml_svmtr_ml_tree_plottr_ml_tunetr_ml_tuning_plottr_ml_xgboosttrama_collection
Dependencies:abindagricolaeAlgDesignbackportsbase64encbitbit64bootbroombslibcachemcarcarDataclicliprclustercolorspacecommonmarkcowplotcpp11crayoncurlDerivdigestdoBydplyremmeansestimabilityfarverfastmapfontawesomeforecastFormulafracdifffsgenericsggplot2gluegtablehmshtmltoolshttpuvisobandjanitorjquerylibjsonlitelabelinglaterlatticelifecyclelme4lmerTestlmtestlubridatemagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamodelrmvtnormnlmenloptrnnetnumDerivotelpatchworkpbkrtestpillarpkgconfigprettyunitsprogresspromisespurrrquantregR6raggrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrreformulasrlangS7sassscalesshinysnakecasesourcetoolsSparseMstringistringrsurvivalsystemfontstextshapingtibbletidyrtidyselecttimechangetimeDatetramatrama.datatrama.modelstrama.viewtzdburcautf8vctrsviridisLitevroomwithrxtablezoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Árvore CART para regressão ou classificação. | tr_ml_cart |
| Carrega um conjunto pequeno para exemplos da coleção ML | tr_ml_example |
| Soma de árvores interpretáveis FIGS. | tr_ml_figs |
| Ajustar um modelo clássico de aprendizado de máquina | tr_ml_fit |
| Floresta aleatória com ranger. | tr_ml_forest |
| Referência linear ou logística binária. | tr_ml_linear |
| Validação cruzada aninhada | tr_ml_nested_cv |
| Gráfico de resíduos de regressão | tr_ml_residuals |
| Regras legíveis de CART ou FIGS | tr_ml_rules |
| Divide dados em treino e teste | tr_ml_split |
| Máquina de vetores de suporte com e1071. | tr_ml_svm |
| Visualizar uma árvore CART, FIGS ou de uma floresta aleatória | tr_ml_tree_plot |
| Ajustar hiperparâmetros por validação cruzada | tr_ml_tune |
| Visualizar o histórico de uma busca de hiperparâmetros | tr_ml_tuning_plot |
| Árvores impulsionadas por gradiente com XGBoost. | tr_ml_xgboost |
| Coleção de aprendizado de máquina supervisionado. | trama_collection |