Man pages for hrvg/RiverML
Machine Learning for River Science
| BMR_res | Benchmark results |
| CA_geology | Geological map of California |
| calibrated_predictions | Calibrate machine learning predictions |
| compute_benchmark | Computes the benchmark in parallel mode |
| compute_final_model | Compute the final models in sequential mode |
| compute_predictions | Retrieve the final (optimal) models |
| drops_streamcat_df | Remove some variables from 'streamcat_df' |
| fixVarNames | Fixes variable names for data visualization purpose |
| fmt_labels | Format the class labels |
| getAllBMRS | Get all the benchmark result in a directory of directories |
| getBestBMRTune | Get the tuning results of the optimal models |
| getBestBMRTuningEntropy | Get the tuning entropy corresponding to the optimal models |
| get_bestBMR_tuning_results | Retrieve the value of the benchmark tuning results |
| get_bestFeatureSets | Get the optinmal feature sets |
| get_BMR | Retrieve benchmark results |
| getBMR_perf_tune | Selecting elements from 'BMR_res' and cosmetic changes |
| getBMRTuningEntropy | Compute the tuning entropy |
| get_calibrations | Performs a posterior multinomial calibration of machine... |
| get_coords | Retrieve the coordinates of the observations |
| get_entropy_df | Formats entropy rate results |
| get_final_learners | Get the final learners from the benchmark tuning results |
| get_final_models | Retrieve the final (optimal) models |
| getFreqBestFeatureSets | Get the frequency of selection of a given feature across all... |
| get_H_rasters | Retrieve rasters of statistical roughness of topography |
| getHyperparNames | Get hyper-parameters names |
| get_inner | Get the inner folds for the nested resampling |
| get_input_data | Loading input data |
| get_input_polygons | Get the polygons for a set of locations defined by... |
| get_learners | Get the learners |
| get_learners_internal | Internal function to get the learners |
| get_outers | Get the outer folds for the nested resampling |
| get_points_from_input_data | Get the SpatialPoint from input data |
| get_pol | Get a SpatialPolygons around a point |
| get_ppc | Get the preprocessing |
| get_predictions | Get predictions |
| get_ps | Get the values for the hyper-parameter(s) set |
| get_smote_coords | Produces noisy coordinates for SMOTE data |
| get_smote_data | Resolve the class imbalance using the SMOTE algorithm |
| get_stats_df | Wrapper function to calculate terrain analysis statistics for... |
| get_streamcat_df | Get the StreamCat data |
| get_target_data | Load target features |
| get_target_points | Extracts mid-points from streamlines |
| get_target_streamcat_df | Matches 'streamcat_df' and 'target_streamlines' using 'COMID' |
| get_target_streamlines | Load a SpatialLinesDataFrame containing values for valley... |
| get_terrain_metrics | Get the terrain analysis metrics |
| get_training_data | Load training features |
| getTunePlot | Plot the distribution of hyper-parameters resulting from the... |
| HPC_optim | Computes an optimized repartition of the HPC computing |
| join_streamlines_with_H_rasters | Extract the values of all H_rasters along streamlines |
| makeAllFeatureImportancePlotFS | Create feature importance across all regions of study |
| makeAverageAccPlot | Make average accuracy plot |
| makeAverageAUCPlot | Make average AUC plot |
| makeBestTuneAUCPlot | Make a violin plot comparing the results from the optimal... |
| makeExampleModelSelectionPlot | Make an example plot of model selection |
| makeFeatureImportancePlot | Makes a dot chart of feature importance |
| makeTotalTimetrainPlot | Make training time plot |
| make_training_data | Transform training data from 'list' to 'data.frame' |
| makeTuningEntropyPlot | Create a plot of the evolution of tuning entropy with the... |
| makeWindowInfluencePlot | Visualize the influence of window size on model selection |
| near_channel_stats | Derive near-channel statistics: "median","mean", "min",... |
| normH | Calculates entropy |
| preproc_data | Process the data according to a 'preProcess' object |
| raster_stats | Derive raster statistics: "median","mean", "min", "max",... |
| regional_benchmark | Wrapper function to compute the benchmark |
| regional_characteristics | Regional characteristics |
| resolve_class_imbalance | Resolve class imbalances using 'UBL' package |
| richness | Calculate the richness (number of different species) |
| sanitize_data | Ensures that non-finite values are flagged as 'NA' |
| savePARAMETERS | Saves the benchmark parameters |
| SFE_all_data_df | Target data for SFE region |
| shannon_weiner | Calculates Shannon-Weiner entropy |
| simpson_evenness | Calculate Simpson's evenness |
| snap_points_to_points | Snaps points to points |
| target_streamlines_K | Target streamlines for the K region |
| target_streamlines_NC | Target streamlines for the NC region |
| target_streamlines_NCC | Target streamlines for the NCC region |
| target_streamlines_SAC | Target streamlines for the SAC region |
| target_streamlines_SC | Target streamlines for the SC region |
| target_streamlines_SCC | Target streamlines for the SCC region |
| target_streamlines_SECA | Target streamlines for the SECA region |
| target_streamlines_SFE | Target streamlines for the SFE region |
| target_streamlines_SJT | Target streamlines for the SJT region |
| terrain_ | Modified 'terrain()' function |
