Package: MSML 1.0.0.1
MSML: Model Selection Based on Machine Learning (ML)
Model evaluation based on a modified version of the recursive feature elimination algorithm. This package is designed to determine the optimal model(s) by leveraging all available features.
Authors:
MSML_1.0.0.1.tar.gz
MSML_1.0.0.1.zip(r-4.5)MSML_1.0.0.1.zip(r-4.4)MSML_1.0.0.1.zip(r-4.3)
MSML_1.0.0.1.tgz(r-4.4-any)MSML_1.0.0.1.tgz(r-4.3-any)
MSML_1.0.0.1.tar.gz(r-4.5-noble)MSML_1.0.0.1.tar.gz(r-4.4-noble)
MSML_1.0.0.1.tgz(r-4.4-emscripten)MSML_1.0.0.1.tgz(r-4.3-emscripten)
MSML.pdf |MSML.html✨
MSML/json (API)
| # Install 'MSML' in R: |
| install.packages('MSML', repos = c('https://mommy003.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mommy003/msml/issues
Datasets:
- cov_train - 3 sets of covariates for training data set
- cov_valid - 3 sets of covariates for validation data set
- data_test - 7 sets of PRSs for test dataset and target phenotype
- data_train - 7 sets of PRSs for training data set and target phenotype
- data_valid - 7 sets of PRSs for validation dataset and target phenotype
- predict_validation - Target phenotype and 127 sets of model configurations based on validation dataset
Last updated 5 months agofrom:f1efe2aadf. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-win | OK | Oct 27 2024 |
| R-4.5-linux | OK | Oct 27 2024 |
| R-4.4-win | OK | Oct 27 2024 |
| R-4.4-mac | OK | Oct 27 2024 |
| R-4.3-win | OK | Oct 27 2024 |
| R-4.3-mac | OK | Oct 27 2024 |
Exports:model_configurationmodel_configuration2model_evaluation
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| 3 sets of covariates for training data set | cov_train |
| 3 sets of covariates for validation data set | cov_valid |
| 7 sets of PRSs for test dataset and target phenotype | data_test |
| 7 sets of PRSs for training data set and target phenotype | data_train |
| 7 sets of PRSs for validation dataset and target phenotype | data_valid |
| model_configuration function | model_configuration |
| model_configuration2 function | model_configuration2 |
| model_evaluation function | model_evaluation |
| target phenotype and 127 sets of model configurations based on validation dataset | predict_validation |
