Man pages for kforthman/caretStack
Stacks models from the caret package to create a more robust prediction
| caretModels | Build a caret model |
| Circbar | Create a circular bar plot |
| comb_outer | Combine results from parallelized outer loop. |
| comb_rep | Combine results from parallelized replication (outer) loop |
| dummy.code.data | Convert categorical predictors to dummy coding |
| is.nan.data.frame | Check NaN for Data.Frame |
| ML.similarity | No title |
| modelPerf | No Description. |
| modelPerf.summ | No Description. |
| pdEst | No Description. |
| pdNCV | Partial-depedence plots using repeated nested CV objects... |
| permTest | No Description. |
| PermTest.rNCV | No Description. |
| PermuPerf.rNCV | No Description. |
| permuPred | No Description. |
| plot.perf | No Description. |
| postResample | No Description. |
| predict_one | Wrapper for executing the rNCV function. |
| predict_two | Wrapper for executing the rNCV function, version 2. |
| PredVal | Predictive Values of Each Base Learner in Each Data Set |
| reorder_cormat | A function to print similarity across ML predictions. |
| rNCV | Repeated, Nested Cross-Validation |
| rNCV.perf.summ | Summarize model performance in rNCV |
| rNCV.perm | rNCV.perm is identical to rNCV except do instead of dopar |
| stackPred | Predict a new set of data using a caretStack model. |
| summarize_one | Plot ML Results and Summary |
| summary_plot | Create a plot describing model performance |
| trans.counts | No Description. |
| VarImp | Variable importance for stack models |
| varimp_plot | Plots variable importance from ML model |
| varImp_rNCV | Variable importance for repeated nested CV. |
