Man pages for environmentalinformatics-marburg/gpm
Geospatial predictive modeling using parameterized and unparameterized models.
| classifyData | Classification of remote sensing data |
| cleanPredictors | Clean predictor variables regarding corelation and variance |
| compContTests | Compute contingency tests for all model responses |
| compIndexFolds | Create testing and training folds for each response variable... |
| compRegrTests | Compute regression tests over all model responses |
| compVarImp | Compute variable importance over all model responses and... |
| createFolds | Create testing and training folds for each response variable. |
| createGPMMeta | Create a meta information dataset in gpm format |
| createIndexFolds | Create testing and training folds for each response variable... |
| deprecated_trainModelffs | Train machine learning model using forward feature selection |
| gpm | Create a gpm object |
| GPM-class | An S4 class to represent a complete gmp dataset |
| GPMData-class | An S4 class to represent gpm data layers |
| gpmInfo | Get or access gpm object information used by various... |
| GPMLog-class | An S4 class to represent gpm log data |
| GPMMeta-class | An S4 class to represent gpm metadata information |
| GPMModel-class | An S4 class to represent gpm model layers |
| gpm-package | Geospatial predictive modeling using parameterized and... |
| helpCalcConTab | Compute contingency table |
| helpCalcKappa | Calculate various kappa coefficients |
| helpStandardError | Calculate the standard error of the mean |
| imputeData | Impute missing data |
| incl | Compute similarity index |
| lutInfo | Get or access internal LUT values used by various functions |
| minimumOccurence | Select features based on minimum occurence across unique... |
| pck_lut | Function used to create sysdata.rda (i.e. LUT) |
| plotClassPerformance | Plot performance of a classification model |
| plotModelCV | Plot cross-validated variable importance |
| plotVarImp | Plot mean variable importance over all model responses |
| plotVarImpHeatmap | Plot mean variable importance over all model responses as... |
| resamplingsByVariable | Create identical samples or resample by specific selector... |
| sampleBy | sample a Spatial*DataFrame by according to a factorial column |
| splitMultResp | Split dataset into testing and training samples individually... |
| splitMultRespLSO | Split dataset into testing and training samples individually... |
| trainModel | Model training and performance using cross-validation |
| trainModelrfe | Train machine learning model |
| trainModelVarSelSD | Extract cross-validated important variables |
