Man pages for biocsuwb/EnsembleFS-package
Ensemble feature selection methods for analysis of molecular data
| build.model.crossval | Train model Random Forest |
| corelation.removed | Function to remove highly correlated variables |
| corelation.search | Function to search highly correlated variables |
| cross.val | Cross-validation |
| ensembleFS | Run end-to-end Ensemble for comparison of feature selection... |
| feature.selection | Selection of features |
| feature.selection.cv | Selection of features in cross-validation |
| fs.mcfs | Monte Carlo Feature Selection |
| fs.mdfs.1D | Build MultiDimensional Feature Selector from IGs |
| fs.mdfs.2D | Build MultiDimensional Feature Selector from IGs uses GPU, is... |
| fs.mrmr | Minimum Redundancy Maximal Relevancy |
| fs.utest | Test U Manna-Whitneya (U-test) for feature selection |
| get.info.gprofiler | Getting information about genes from gprogiler2 |
| get.info.top.gene | Getting information about top genes from gprogiler2 |
| get.top.gene | Get the best genes |
| graph.result | Showing result ensemble |
| list.methods | List methods |
| model.result.top.var | Train model Random Forest for the top-N variables N =... |
| ranking.feature | Function for ranking selected variables |
| stability.selection.top.var | Compute Lustgarten's stability measure ASM (N) dependence for... |
| stabilty.selection | Compute Lustgarten’s stability measure |
