Man pages for rtemis
Schema-Driven Machine Learning and Visualization
| ai_review | Write an assessment of a model review with a language model |
| applicable_metrics | Which Decomposition Metrics Apply to Which Algorithm |
| apply_decomp | Apply Decomposition to New Data |
| apply_preprocessor | Apply trained Preprocessor to new data |
| available_algorithms | Available Algorithms |
| bias_variance | Estimate Bias and Variance |
| calibrate | Calibrate 'Classification' & 'ClassificationRes' Models |
| check_data | Check Data |
| classification_metrics | Classification Metrics |
| class_imbalance | Class Imbalance |
| cluster | Perform Clustering |
| conformal | Conformal prediction regions |
| conformal_metrics | Score a Conformal Prediction Region |
| data_fingerprint | Fingerprint a dataset |
| data_profile | Profile a dataset |
| ddb_collect | Collect a lazy-read duckdb table |
| ddb_data | Read CSV using DuckDB |
| decomp | Perform Data Decomposition |
| decomp_metrics | Decomposition Metrics |
| decomposition_traits | Decomposition Algorithm Traits |
| describe | Describe object |
| df_movecolumn | Move data frame column |
| df_nunique_perfeat | Unique values per feature |
| dot-drop_meta_keys | Drop JSON document metadata keys from a parsed config list |
| dot-get_alg_name | Resolve a supervised algorithm name |
| dot-get_clust_name | Resolve a clustering algorithm name |
| dot-get_decom_name | Resolve a decomposition algorithm name |
| dot-list_to_ClusteringConfig | Convert a list to a ClusteringConfig object |
| dot-list_to_DecompositionConfig | Convert a list to a DecompositionConfig object |
| dot-list_to_Hyperparameters | Convert a list to a Hyperparameters object |
| dot-list_to_PreprocessorConfig | Convert a list to a PreprocessorConfig object |
| dot-list_to_ResamplerConfig | Convert a list to a ResamplerConfig object |
| dot-list_to_SuperConfig | Convert a list to a 'SuperConfig' object |
| dot-list_to_SupervisedPreprocessorConfig | Convert a list to a SupervisedPreprocessorConfig object |
| dot-list_to_TunerConfig | Convert a list to a TunerConfig object |
| dot-supervised_algorithms | Supervised algorithm catalog |
| draw_linad | Plot a Linear Additive Tree |
| dt_describe | Describe data.table |
| dt_inspect_types | Inspect column types |
| dt_keybin_reshape | Long to wide key-value reshaping |
| dt_merge | Merge data.tables |
| dt_names_by_attr | List column names by attribute |
| dt_nunique_perfeat | Number of unique values per feature |
| dt_pctmatch | Get N and percent match of values between two columns of two... |
| dt_pctmissing | Get percent of missing values from every column |
| dt_set_autotypes | Set column types automatically |
| dt_set_clean_all | Clean column names and factor levels _*in-place*_ |
| dt_set_cleanfactorlevels | Clean factor levels of data.table _*in-place*_ |
| dt_set_logical2factor | Convert data.table logical columns to factors |
| dt_set_one_hot | Convert data.table's factor to one-hot encoding _*in-place*_ |
| exc | Exclude columns by character or numeric vector. |
| explain | Explain a prediction |
| explanation_methods | Explanation Methods per Algorithm |
| feature_matrix | Convert tabular data to feature matrix |
| feature_names | Get feature names |
| features | Get features from tabular data |
| fit_predict | Fit a Learner and Predict New Data |
| fitted_config | A 'Preprocessor"s config with its learned values filled in |
| get_factor_names | Get factor names |
| get_learning_curve | Learning curve of a fitted model |
| get_metrics | Get metrics |
| get_mode | Get the mode of a factor or integer |
| getnames | Get names by string matching or class |
| getnamesandtypes | Get data.frame names and types |
| get_varimp | Get variable importance |
| grapes-BC-grapes | Binary matrix times character vector |
| HyperparameterCandidates | The values a tuner may choose among for one hyperparameter |
| inc | Select (include) columns by character or numeric vector. |
| index_col_by_attr | Index columns by attribute name & value |
| ingest | Read a data file and normalize it to Parquet |
| init_project_dir | Initialize Project Directory |
| inspect | Inspect rtemis object |
| inspect_type | Inspect character and factor vector |
| is_constant | Check if vector is constant |
| is_wire_hyperparameters_set | Is this parsed JSON a set of hyperparameters? |
| JSONSchema_to_S7 | Build an S7 class from a JSON Schema |
| massGLM | Mass-univariate GLM Analysis |
| matchcases | Match cases by covariates |
| mgetnames | Get names by string matching multiple patterns |
| names_by_class | List column names by class |
| numeric_features | Get numeric features from tabular data |
| one_hot2factor | Convert one-hot encoded matrix to factor |
| outcome | Get the outcome as a vector |
| outcome_name | Get the name of the last column |
| partition | Split a dataset into training and held-out test partitions |
| plot_learning | Plot a Model's Learning Curve |
| plot_manhattan | Plot a MassGLM Result |
| plot_metric | Plot Stored Metrics Across Model Resamples |
| plot_roc | Plot Classification ROC Curves |
| plot_session | Plot a Supervised object's session timeline |
| plot_true_pred | Plot a Model's True Versus Predicted Values |
| plot_varimp | Plot a Model's Variable Importance |
| preprocess | Preprocess Data |
| preprocessed | Get preprocessed data from 'Preprocessor'. |
| present | Describe and Plot Fitted Models |
| read | Read tabular data from a variety of formats |
| read_config | Read an rtemis config from file |
| read_result | Read a portable result from a local schema registry |
| reconstruct | Reconstruct Data from a Decomposition |
| record | Derive a run record from a fitted model |
| reexports | Objects exported from other packages |
| regression_metrics | Regression Metrics |
| resample | Resample data |
| review | Review a trained supervised model |
| rnormmat | Random Normal Matrix |
| roc_curve | ROC curve coordinates |
| rtemis_conditions | rtemis error conditions |
| rtemis-package | 'rtemis': Advanced Machine Learning and Visualization |
| rtversion | Get rtemis version and system info |
| runifmat | Random Uniform Matrix |
| S7_dispatcher_JSONSchema | Generate a config family's dispatcher JSON Schema |
| S7_to_JSONSchema | Convert an S7 class built with prop_* factories to a JSON... |
| same_data | Do two fingerprints identify the same dataset? |
| se | Standard error of the fit |
| session_kind_colors | Session Node Kind Colors |
| session_timeline | Session Execution Timeline Table |
| setdiffsym | Symmetric Set Difference |
| set_outcome | Move outcome to last column |
| set_positive_class | Set positive class |
| setup_ARFFIngest | Set up an 'ARFFIngestConfig' |
| setup_ASWCriterion | Setup ASWCriterionConfig |
| setup_Autoencoder | Setup Autoencoder config. |
| setup_BART | Setup BART Hyperparameters |
| setup_Bootstrap | Setup Bootstrap Resampler |
| setup_CART | Setup CART Hyperparameters |
| setup_CHCriterion | Setup CHCriterionConfig |
| setup_ClusterConfig | Setup ClusterConfig |
| setup_CMeans | Setup CMeansConfig |
| setup_ConditionalSuperLearner | Setup ConditionalSuperLearner Hyperparameters |
| setup_CQR | Setup Conformalized Quantile Regression |
| setup_CUDA | Setup an NVIDIA GPU as the compute device |
| setup_Custom | Setup Custom Resampler |
| setup_CVPlus | Setup CV+ Conformal Prediction |
| setup_DBSCAN | Setup DBSCANConfig |
| setup_DecomposeConfig | Setup DecomposeConfig |
| setup_DelimitedIngest | Set up a 'DelimitedIngestConfig' |
| setup_DTAIngest | Set up a 'DTAIngestConfig' |
| setup_FutureExecution | Set up a 'FutureExecutionConfig' |
| setup_GAM | Setup GAM Hyperparameters |
| setup_GLM | Setup GLM Hyperparameters |
| setup_GLMNET | Setup GLMNET Hyperparameters |
| setup_GLMTree | Setup GLMTree Hyperparameters |
| setup_GMM | Setup GMMConfig |
| setup_GridSearch | Setup Grid Search Config |
| setup_GroupPartition | Set up a 'GroupPartitionConfig' |
| setup_HAL | Setup HAL Hyperparameters |
| setup_HardCL | Setup HardCLConfig |
| setup_HOPACH | Setup HOPACHConfig |
| setup_ICA | setup_ICA |
| setup_Isomap | Setup Isomap config. |
| setup_Isotonic | Setup Isotonic Hyperparameters |
| setup_KFold | Setup KFold Resampler |
| setup_KMeans | Setup KMeansConfig |
| setup_KNN | Setup KNN Hyperparameters |
| setup_LightCART | Setup LightCART Hyperparameters |
| setup_LightGBM | Setup LightGBM Hyperparameters |
| setup_LightRF | Setup LightRF Hyperparameters |
| setup_LightRuleFit | Setup LightRuleFit Hyperparameters |
| setup_LINAD | Setup LINAD Hyperparameters |
| setup_LINADForest | Setup LINADForest Hyperparameters |
| setup_LinearSVM | Setup LinearSVM Hyperparameters |
| setup_LOOCV | Setup LOOCV Resampler |
| setup_MARS | Setup MARS Hyperparameters |
| setup_MDS | Setup MDS config. |
| setup_MiraiExecution | Set up a 'MiraiExecutionConfig' |
| setup_MLP | Setup MLP Hyperparameters |
| setup_ModalityStacking | Setup ModalityStacking Hyperparameters |
| setup_MonotonicHAL | Setup MonotonicHAL Hyperparameters |
| setup_MultiASWCriterion | Setup MultiASWCriterionConfig |
| setup_NeuralGas | Setup NeuralGasConfig |
| setup_NMF | Setup NMF config. |
| setup_NNLS | Setup NNLS Hyperparameters |
| setup_Nystrom | Setup NystromConfig |
| setup_PAM | Setup PAMConfig |
| setup_PAMK | Setup PAMKConfig |
| setup_ParquetIngest | Set up a 'ParquetIngestConfig' |
| setup_PCA | Setup PCA config. |
| setup_PCoA | Setup PCoA config. |
| setup_PredefinedPartition | Set up a 'PredefinedPartitionConfig' |
| setup_Preprocessor | Setup Preprocessor |
| setup_RadialSVM | Setup RadialSVM Hyperparameters |
| setup_RandomPartition | Set up a 'RandomPartitionConfig' |
| setup_Ranger | Setup Ranger Hyperparameters |
| setup_RDSIngest | Set up an 'RDSIngestConfig' |
| setup_Resampler | Setup a Resampler (Deprecated) |
| setup_SerialExecution | Set up a 'SerialExecutionConfig' |
| setup_SHAP | Setup SHAP Explanation |
| setup_SpectralLaplace | Setup SpectralLaplaceConfig |
| setup_SpectralLocal | Setup SpectralLocalConfig |
| setup_SpectralRBF | Setup SpectralRBFConfig |
| setup_SplitConformal | Setup Split Conformal Prediction |
| setup_SPLS | Setup SPLS Hyperparameters |
| setup_StratBoot | Setup StratBoot Resampler |
| setup_StratSub | Setup StratSub Resampler |
| setup_SuperConfig | Setup SuperConfig |
| setup_SuperConfigLive | Setup SuperConfigLive |
| setup_SuperLearner | Setup SuperLearner Hyperparameters |
| setup_SupervisedPreprocessor | Setup Supervised Preprocessor |
| setup_TabNet | Setup TabNet Hyperparameters |
| setup_TimePartition | Set up a 'TimePartitionConfig' |
| setup_tSNE | Setup tSNE config. |
| setup_UMAP | Setup UMAP config. |
| setup_VariationalAutoencoder | Setup Variational Autoencoder config. |
| setup_XLSXIngest | Set up an 'XLSXIngestConfig' |
| shap_by_level | Contributions of a categorical feature, by the level each... |
| shap_case | One case's contributions, ordered by how much they moved the... |
| shap_long | Every contribution, one row per case per feature |
| show_color_key | Show rtemis color key |
| size | Size of object |
| table_column_attr | Tabulate column attributes |
| to_json | Convert to JSON-serializable list |
| to_markdown | Render a report as Markdown |
| train | Train Supervised Learning Models |
| tune_over | Mark the values to tune a hyperparameter over |
| tuning_grid | Tuning grid of a Hyperparameters object |
| validate_config | Validate an rtemis config, against the schema and optionally... |
| varimp_table | Variable importance as one table |
| write_config | Write an rtemis config to a JSON file |
| write_record | Write a run record to a JSON file |
| write_result | Write a portable result with optional Parquet payloads |
| write_text | Write a report as text |
| writeup | Write the Methods and Results sections for a trained model |
