Schema-Driven Machine Learning and Visualization

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Documentation for package ‘rtemis’ version 1.4.2

• DESCRIPTION file
• Package NEWS
• Package README

Help Pages

A B C D E F G H I J M N O P R S T V W misc

rtemis-package

'rtemis': Advanced Machine Learning and Visualization

-- A --

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
available_calibration	Available Algorithms
available_clustering	Available Algorithms
available_decomposition	Available Algorithms
available_supervised	Available Algorithms

-- B --

bias_variance

Estimate Bias and Variance

-- C --

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

-- D --

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
decomposition_traits	Decomposition Algorithm Traits
decomp_metrics	Decomposition Metrics
describe	Describe object
df_movecolumn	Move data frame column
df_nunique_perfeat	Unique values per feature
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 data.tables
dt_pctmissing	Get percent of missing values from every column
dt_set_autotypes	Set column types automatically
dt_set_cleanfactorlevels	Clean factor levels of data.table _*in-place*_
dt_set_clean_all	Clean column names and factor levels _*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*_

-- E --

exc	Exclude columns by character or numeric vector.
explain	Explain a prediction
explanation_methods	Explanation Methods per Algorithm

-- F --

features	Get features from tabular data
feature_matrix	Convert tabular data to feature matrix
feature_names	Get feature names
fitted_config	A 'Preprocessor"s config with its learned values filled in
fit_predict	Fit a Learner and Predict New Data

-- G --

getcharacternames	Get names by string matching or class
getdatenames	Get names by string matching or class
getfactornames	Get names by string matching or class
getlogicalnames	Get names by string matching or class
getnames	Get names by string matching or class
getnamesandtypes	Get data.frame names and types
getnumericnames	Get names by string matching or class
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
get_varimp	Get variable importance

-- H --

HyperparameterCandidates

The values a tuner may choose among for one hyperparameter

-- I --

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

-- J --

JSONSchema_to_S7

Build an S7 class from a JSON Schema

-- M --

massGLM	Mass-univariate GLM Analysis
matchcases	Match cases by covariates
mgetnames	Get names by string matching multiple patterns

-- N --

names_by_class	List column names by class
numeric_features	Get numeric features from tabular data

-- O --

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

-- P --

partition	Split a dataset into training and held-out test partitions
plot.MassGLM	Plot a MassGLM Result
plot_learning	Plot a Model's Learning Curve
plot_manhattan	Plot a MassGLM Result
plot_manhattan.MassGLM	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

-- R --

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
regression_metrics	Regression Metrics
resample	Resample data
review	Review a trained supervised model
rnormmat	Random Normal Matrix
roc_curve	ROC curve coordinates
rtemis	'rtemis': Advanced Machine Learning and Visualization
rtemis-deprecated	Setup a Resampler (Deprecated)
rtemis_conditions	rtemis error conditions
rtemis_data_error	rtemis error conditions
rtemis_dim_error	rtemis error conditions
rtemis_error	rtemis error conditions
rtemis_file_exists	rtemis error conditions
rtemis_file_not_found	rtemis error conditions
rtemis_input_error	rtemis error conditions
rtemis_io_error	rtemis error conditions
rtemis_length_error	rtemis error conditions
rtemis_level_mismatch	rtemis error conditions
rtemis_missing_data	rtemis error conditions
rtemis_null_input	rtemis error conditions
rtemis_outcome_error	rtemis error conditions
rtemis_range_error	rtemis error conditions
rtemis_runtime_error	rtemis error conditions
rtemis_type_error	rtemis error conditions
rtemis_unsupported_error	rtemis error conditions
rtemis_value_error	rtemis error conditions
rtversion	Get rtemis version and system info
runifmat	Random Uniform Matrix

-- S --

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 Schema
same_data	Do two fingerprints identify the same dataset?
se	Standard error of the fit
session_timeline	Session Execution Timeline Table
setdiffsym	Symmetric Set Difference
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'
set_outcome	Move outcome to last column
set_positive_class	Set positive class
shap_by_level	Contributions of a categorical feature, by the level each case has
shap_case	One case's contributions, ordered by how much they moved the prediction
shap_long	Every contribution, one row per case per feature
show_color_key	Show rtemis color key
size	Size of object

-- T --

table_column_attr	Tabulate column attributes
train	Train Supervised Learning Models
tune_over	Mark the values to tune a hyperparameter over
tuning_grid	Tuning grid of a Hyperparameters object

-- V --

validate_config	Validate an rtemis config, against the schema and optionally against data
varimp_table	Variable importance as one table

-- W --

writeup	Write the Methods and Results sections for a trained model
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

-- misc --

%BC%	Binary matrix times character vector