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Showing 1 of 3 files from the diff.
R/MetaForest.R
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man/MetaForest.Rd
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cran-comments.md
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@@ -63,7 +63,7 @@
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| 63 | 63 | #' are thus included in the same cross-validation sample. Then, two random |
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| 64 | 64 | #' forests are grown on these cross-validation samples, and for each random |
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| 65 | 65 | #' forest, the other sample is used to calculate prediction error and variable |
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| 66 | - | #' importance (see \href{http://doi.org/10.1007/s11634-016-0276-4}{Janitza, |
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| 66 | + | #' importance (see \href{https://doi.org/10.1007/s11634-016-0276-4}{Janitza, |
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| 67 | 67 | #' Celik, & Boulesteix, 2016}). |
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| 68 | 68 | #' @import stats |
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| 69 | 69 | #' @import ranger |
2 Commits
| Files | Coverage |
|---|---|
| MF.R | 93.33% |
| MF_cluster.R | 77.08% |
| MetaForest.R | 90.91% |
| ModelInfo_mf.R | 98.51% |
| ModelInfo_rma.R | 0.00% |
| PartialDependence.R | 47.01% |
| SimulateSMD.R | 0.00% |
| VarImpPlot.R | 84.62% |
| WeightedScatter.R | 0.00% |
| coef_test.R | 0.00% |
| extract_proximity.MetaForest.R | 0.00% |
| helpers.R | 11.11% |
| marginal_predictions.R | 46.43% |
| merge_forests.R | 96.88% |
| plot.MetaForest.R | 30.43% |
| predict.MetaForest.R | 71.43% |
| preselect.R | 66.67% |
| print.MetaForest.R | 0.00% |
| print.summary.MetaForest.R | 0.00% |
| summary.MetaForest.R | 90.91% |
| Folder Totals (20 files) | 51.43% |
| Project Totals (20 files) | 51.43% |
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