Man pages for randomrotation/random.rotation
Enhanced Random Rotation Ensembles
| add_noise_columns | Add noise dimensions |
| compute_mode | Mode |
| compute_tuning_parameter | Optimize tuning parameter |
| create_random_rotation_matrix_array | Create an array of random rotations (plus identity) |
| determine_relevant_columns | Get X and Y columns |
| df_apply_random_rotations | Apply an array of random rotations to an input data frame |
| df_convert_cols_to_factor | Convert cols to factor |
| df_convert_cols_to_numeric | Convert cols to numeric |
| df_exclude_cols | Remove cols |
| df_missed_factors | Auto-detect non-factor columns that should be factors |
| df_numeric_strings | Auto-detect fake string columns that should be numeric |
| df_uniqueness_properties | Auto-detect suspicious columns |
| generate_testing_row_indices | Split into train and test 2/2: testing (out-of-sample)... |
| generate_training_row_indices | Split into train and test 1/2: training (in-sample) indices |
| impute | Impute NA values |
| is_sorted | Check if sorted |
| match_columns | Obtain integer indices |
| numeric_cols | Get numeric cols |
| num_trees_per_rot | Compute number of trees per rotation |
| post_sample_preprocessing | Pre-processing of input file (AFTER in-/out-of-sample split) |
| pre_sample_preprocessing | Pre-processing of raw input file (BEFORE in-/out-of-sample... |
| random_rotation_matrix | Random rotation (without flip) |
| random_rotation_matrix_incl_flip | Random rotation (including potential flip) |
| tree_height | Determine height of RF decision tree |
| uni_rank | Apply map |
| weights_cut | Equal-weight top-h rotations |
| weights_exp | Exponential decay in weight for rotations |
| weights_rre | Equal-weight all rotations |
| zero_one_rank_map | Create map |
