Package index • rtemis

All functions

available_supervised() available_clustering() available_decomposition(): Available Algorithms
available_draw(): Available Draw Functions
available_themes(): Print available rtemis themes
calibrate(): Calibrate Classification & ClassificationRes Models
check_data(): Check Data
choose_theme(): Select an rtemis theme
class_imbalance(): Class Imbalance
classification_metrics(): Classification Metrics
clean_colnames(): Clean column names
clean_names(): Clean names
cluster(): Perform Clustering
col2grayscale(): Color to Grayscale
color_adjust(): Adjust HSV Color
ddSci(): Format Numbers for Printing
ddb_collect(): Collect a lazy-read duckdb table
ddb_data(): Read CSV using DuckDB
decomp(): Perform Data Decomposition
describe(): Describe rtemis object
df_movecolumn(): Move data frame column
df_nunique_perfeat(): Unique values per feature
draw_3Dscatter(): Interactive 3D Scatter Plots
draw_bar(): Interactive Barplots
draw_box(): Interactive Boxplots & Violin plots
draw_calibration(): Draw calibration plot
draw_confusion(): Plot confusion matrix
draw_dist(): Draw Distributions using Histograms and Density Plots
draw_fit(): True vs. Predicted Plot
draw_graphD3(): Plot graph using networkD3
draw_graphjs(): Plot network using threejs::graphjs
draw_heatmap(): Interactive Heatmaps
draw_leaflet(): Plot interactive choropleth map using leaflet
draw_pie(): Interactive Pie Chart
draw_protein(): Plot an amino acid sequence with annotations
draw_pvals(): Barplot p-values using draw_bar
draw_roc(): Draw ROC curve
draw_scatter(): Interactive Scatter Plots
draw_spectrogram(): Interactive Spectrogram
draw_survfit(): Draw a survfit object
draw_table(): Simple HTML table
draw_ts(): Interactive Timeseries Plots
draw_varimp(): Interactive Variable Importance Plot
draw_volcano(): Volcano Plot
draw_xt(): Plot timeseries data
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_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.
fct_describe(): Describe factor
feature_matrix(): Convert tabular data to feature matrix
feature_names(): Get feature names
features(): Get features from tabular data
get_factor_names(): Get factor names
get_mode(): Get the mode of a factor or integer
get_palette(): Get Color Palette
getnames() getfactornames() getnumericnames() getlogicalnames() getcharacternames() getdatenames(): Get names by string matching or class
getnamesandtypes(): Get data.frame names and types
`%BC%`: Binary matrix times character vector
inc(): Select (include) columns by character or numeric vector.
index_col_by_attr(): Index columns by attribute name & value
init_project_dir(): Initialize Project Directory
inspect(): Inspect rtemis object
inspect_type(): Inspect character and factor vector
is_constant(): Check if vector is constant
labelify(): Format text for label printing
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
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
plot(<MassGLM>): Plot MassGLM using volcano plot
plot_manhattan() plot_manhattan.MassGLM(): Manhattan plot
plot_roc(): Plot ROC curve
plot_true_pred(): Plot True vs. Predicted Values
plot_varimp(): Plot Variable Importance
preprocess() preprocess.class_tabular.PreprocessorConfig() preprocess.class_tabular.Preprocessor(): Preprocess Data
preprocessed(): Get preprocessed data from Preprocessor.
present(): Present rtemis object
present.list(): Present list of Supervised or SupervisedRes objects
previewcolor(): Preview color
read(): Read tabular data from a variety of formats
read_config(): Read SuperConfig from TOML file
regression_metrics(): Regression Metrics
resample(): Resample data
rnormmat(): Random Normal Matrix
rt_reactable(): View table using reactable
rtemis rtemis-package: rtemis: Advanced Machine Learning and Visualization
rtemis_colors: rtemis Color System
rtversion(): Get rtemis version and system info
runifmat(): Random Uniform Matrix
set_outcome(): Move outcome to last column
setdiffsym(): Symmetric Set Difference
setup_CART(): Setup CART Hyperparameters
setup_CMeans(): Setup CMeansConfig
setup_DBSCAN(): Setup DBSCANConfig
setup_ExecutionConfig(): Setup Execution Configuration
setup_GAM(): Setup GAM Hyperparameters
setup_GLM(): Setup GLM Hyperparameters
setup_GLMNET(): Setup GLMNET Hyperparameters
setup_GridSearch(): Setup Grid Search Config
setup_HardCL(): Setup HardCLConfig
setup_ICA(): setup_ICA
setup_Isomap(): Setup Isomap config.
setup_Isotonic(): Setup Isotonic Hyperparameters
setup_KMeans(): Setup KMeansConfig
setup_LightCART(): Setup LightCART Hyperparameters
setup_LightGBM(): Setup LightGBM Hyperparameters
setup_LightRF(): Setup LightRF Hyperparameters
setup_LightRuleFit(): Setup LightRuleFit Hyperparameters
setup_LinearSVM(): Setup LinearSVM Hyperparameters
setup_NMF(): Setup NMF config.
setup_NeuralGas(): Setup NeuralGasConfig
setup_PCA(): Setup PCA config.
setup_Preprocessor(): Setup Preprocessor
setup_RadialSVM(): Setup RadialSVM Hyperparameters
setup_Ranger(): Setup Ranger Hyperparameters
setup_Resampler(): Setup Resampler
setup_SuperConfig(): Setup SuperConfig
setup_TabNet(): Setup TabNet Hyperparameters
setup_UMAP(): Setup UMAP config.
setup_tSNE(): Setup tSNE config.
size(): Size of object
table_column_attr(): Tabulate column attributes
theme_black() theme_blackgrid() theme_blackigrid() theme_darkgray() theme_darkgraygrid() theme_darkgrayigrid() theme_white() theme_whitegrid() theme_whiteigrid() theme_lightgraygrid() theme_mediumgraygrid(): Themes for draw_* functions
train(): Train Supervised Learning Models
uniprot_get(): Get protein sequence from UniProt
validate_hyperparameters(): Check hyperparameters given training data
write_toml() write_toml.SuperConfig(): Write to TOML file
xt_example: Example longitudinal dataset
xtdescribe(): Describe longitudinal dataset