Man pages for pat-s/2019-feature-selection
Research Compendium package for the publication "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"
| calc_nri_indices | Calculate Normalized Ratio Indices |
| calculate_vi | calculate_vi |
| calc_veg_indices | Calculate vegetation indices |
| copy_cloud | copy_cloud |
| create_defoliation_map | write_defoliation_map |
| create_prediction_df | create_prediction_df |
| create_prediction_map | Create spatial maps from the predicted data |
| data_preprocessing | Data preprocessing |
| download | Download data |
| download_images | download_images |
| extract_to_plot | Extract hyperspectral bands |
| extra_to_plot | Extract indices |
| feature_imp_parallel | Parallel feature importance wrapper |
| FeatureSelection-package | FeatureSelection: Research Compendium package for the... |
| file_cp_ts | Copy a file to a new location conditionally |
| get_coordinates | get_coordinates |
| get_records | get_records |
| inv_boxcox_rmse | Reverse Boxcox transformation |
| mask_mosaic | mask_mosaic |
| mask_vi | mask_vi |
| mosaic_clouds | mosaic_clouds |
| mosaic_images | mosaic_images |
| my_pairs | EDA functions from A. Brenning |
| predict_defoliation | predict_defoliation |
| prediction_raster | prediction_raster |
| process_hyperspec | process_hyperspec |
| ras_to_sf | ras_to_sf |
| scale_defoliation | write_defoliation_map |
| stack_bands | stack_bands |
| train_wrapper | Create a mlr train wrapper |
| tune_ctrl_mbo_30n_70it | mlrMBO 30n 70 iterations tuning setting |
| tune_ctrl_wrapper | Create a mlr tune control object |
| tune_wrapper | Create a mlr tune wrapper |
| unzip_images | download_images |
