Package: rtemis 1.2.0

E.D. Gennatas

rtemis: Machine Learning and Visualization

Machine learning and visualization package with an 'S7' backend featuring comprehensive type checking and validation, paired with an efficient functional user-facing API. train(), cluster(), and decomp() provide one-call access to supervised and unsupervised learning. All configuration steps are performed using setup functions and validated. A single call to train() handles preprocessing, hyperparameter tuning, and testing with nested resampling. Supports 'data.frame', 'data.table', and 'tibble' inputs, parallel execution, and interactive visualizations. The package first appeared in E.D. Gennatas (2017) <https://repository.upenn.edu/entities/publication/d81892ea-3087-4b71-a6f5-739c58626d64>.

Authors:E.D. Gennatas [aut, cre, cph]

rtemis_1.2.0.tar.gz
rtemis_1.2.0.zip(r-4.7)rtemis_1.2.0.zip(r-4.6)rtemis_1.2.0.zip(r-4.5)
rtemis_1.2.0.tgz(r-4.6-any)rtemis_1.2.0.tgz(r-4.5-any)
rtemis_1.2.0.tar.gz(r-4.7-any)rtemis_1.2.0.tar.gz(r-4.6-any)
rtemis_1.0.1.tgz(r-4.5-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rtemis/json (API)

# Install 'rtemis' in R:
install.packages('rtemis', repos = c('https://ictml-project.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/rtemis-org/rtemis/issues

Pkgdown/docs site:https://docs.rtemis.org

Datasets:

On CRAN:

Conda:

data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization

8.02 score 148 stars 2 packages 45 scripts 535 downloads 162 exports 13 dependencies

Last updated from:ee040e1ef7. Checks:8 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK319
source / vignettesOK356
linux-release-x86_64OK357
macos-release-arm64OK176
macos-oldrel-arm64OK167
windows-develOK667
windows-releaseOK719
windows-oldrelOK658
wasm-releaseFAIL212

Exports:.list_to_Hyperparameters.list_to_ResamplerConfig.list_to_TunerConfig%BC%available_clusteringavailable_decompositionavailable_drawavailable_supervisedavailable_themescalibratecheck_datachoose_themeclass_imbalanceclassification_metricsclean_colnamesclean_namesclustercol2grayscalecolor_adjustddb_collectddb_dataddScidecompdescribedf_movecolumndf_nunique_perfeatdraw_3Dscatterdraw_bardraw_boxdraw_calibrationdraw_confusiondraw_distdraw_fitdraw_graphD3draw_graphjsdraw_heatmapdraw_leafletdraw_piedraw_proteindraw_pvalsdraw_rocdraw_scatterdraw_spectrogramdraw_survfitdraw_tabledraw_tsdraw_varimpdraw_volcanodraw_xtdt_describedt_inspect_typesdt_keybin_reshapedt_mergedt_names_by_attrdt_nunique_perfeatdt_pctmatchdt_pctmissingdt_set_autotypesdt_set_clean_alldt_set_cleanfactorlevelsdt_set_logical2factordt_set_one_hotexcfeature_matrixfeature_namesfeaturesget_factor_namesget_modeget_msg_sinkget_palettegetcharacternamesgetdatenamesgetfactornamesgetlogicalnamesgetnamesgetnamesandtypesgetnumericnamesincindex_col_by_attrinit_project_dirinspectinspect_typeis_constantlabelifymassGLMmatchcasesmgetnamesnames_by_classone_hot2factoroutcomeoutcome_nameplot_manhattanplot_manhattan.MassGLMplot_rocplot_true_predplot_varimppreprocesspreprocess.class_tabular.Preprocessorpreprocess.class_tabular.PreprocessorConfigpreprocessedpresentpreviewcolorreadread_configregression_metricsresamplernormmatrtemis_colorsrtversionrunifmatset_msg_sinkset_outcomesetdiffsymsetup_CARTsetup_CMeanssetup_DBSCANsetup_ExecutionConfigsetup_GAMsetup_GLMsetup_GLMNETsetup_GridSearchsetup_HardCLsetup_ICAsetup_Isomapsetup_Isotonicsetup_KMeanssetup_LightCARTsetup_LightGBMsetup_LightRFsetup_LightRuleFitsetup_LinearSVMsetup_NeuralGassetup_NMFsetup_PCAsetup_Preprocessorsetup_RadialSVMsetup_Rangersetup_Resamplersetup_SuperConfigsetup_SuperConfigLivesetup_TabNetsetup_tSNEsetup_UMAPsizetable_column_attrtheme_blacktheme_blackgridtheme_blackigridtheme_darkgraytheme_darkgraygridtheme_darkgrayigridtheme_lightgraygridtheme_mediumgraygridtheme_whitetheme_whitegridtheme_whiteigridto_jsontrainuniprot_getwith_msg_sinkwrite_tomlxtdescribe

Dependencies:base64encclicodetoolsdata.tabledigestfastmapfutureglobalshtmltoolslistenvparallellyrlangS7

Readme and manuals

Help Manual

Help pageTopics
'rtemis': Advanced Machine Learning and Visualizationrtemis-package rtemis
Binary matrix times character vector%BC%
Available Draw Functionsavailable_draw
Available Algorithmsavailable_algorithms available_clustering available_decomposition available_supervised
Print available 'rtemis' themesavailable_themes
Calibrate 'Classification' & 'ClassificationRes' Modelscalibrate
Check Datacheck_data
Select an rtemis themechoose_theme
Class Imbalanceclass_imbalance
Classification Metricsclassification_metrics
Clean column namesclean_colnames
Clean namesclean_names
Perform Clusteringcluster
Color to Grayscalecol2grayscale
Adjust HSV Colorcolor_adjust
Collect a lazy-read duckdb tableddb_collect
Read CSV using DuckDBddb_data
Format Numbers for PrintingddSci
Perform Data Decompositiondecomp
Describe objectdescribe
Move data frame columndf_movecolumn
Unique values per featuredf_nunique_perfeat
Interactive 3D Scatter Plotsdraw_3Dscatter
Interactive Barplotsdraw_bar
Interactive Boxplots & Violin plotsdraw_box
Draw calibration plotdraw_calibration
Plot confusion matrixdraw_confusion
Draw Distributions using Histograms and Density Plotsdraw_dist
True vs. Predicted Plotdraw_fit
Plot graph using 'networkD3'draw_graphD3
Plot network using 'threejs::graphjs'draw_graphjs
Interactive Heatmapsdraw_heatmap
Plot interactive choropleth map using 'leaflet'draw_leaflet
Interactive Pie Chartdraw_pie
Plot an amino acid sequence with annotationsdraw_protein
Barplot p-values using draw_bardraw_pvals
Draw ROC curvedraw_roc
Interactive Scatter Plotsdraw_scatter
Interactive Spectrogramdraw_spectrogram
Draw a survfit objectdraw_survfit
Simple HTML tabledraw_table
Interactive Timeseries Plotsdraw_ts
Interactive Variable Importance Plotdraw_varimp
Volcano Plotdraw_volcano
Plot timeseries datadraw_xt
Describe data.tabledt_describe
Inspect column typesdt_inspect_types
Long to wide key-value reshapingdt_keybin_reshape
Merge data.tablesdt_merge
List column names by attributedt_names_by_attr
Number of unique values per featuredt_nunique_perfeat
Get N and percent match of values between two columns of two data.tablesdt_pctmatch
Get percent of missing values from every columndt_pctmissing
Set column types automaticallydt_set_autotypes
Clean column names and factor levels _*in-place*_dt_set_clean_all
Clean factor levels of data.table _*in-place*_dt_set_cleanfactorlevels
Convert data.table logical columns to factorsdt_set_logical2factor
Convert data.table's factor to one-hot encoding _*in-place*_dt_set_one_hot
Exclude columns by character or numeric vector.exc
Convert tabular data to feature matrixfeature_matrix
Get feature namesfeature_names
Get features from tabular datafeatures
Get factor namesget_factor_names
Get the mode of a factor or integerget_mode
Get the current rtemis message sinkget_msg_sink
Get Color Paletteget_palette
Get names by string matching or classgetcharacternames getdatenames getfactornames getlogicalnames getnames getnumericnames
Get data.frame names and typesgetnamesandtypes
Select (include) columns by character or numeric vector.inc
Index columns by attribute name & valueindex_col_by_attr
Initialize Project Directoryinit_project_dir
Inspect rtemis objectinspect
Inspect character and factor vectorinspect_type
Check if vector is constantis_constant
Format text for label printinglabelify
Mass-univariate GLM AnalysismassGLM
Match cases by covariatesmatchcases
Get names by string matching multiple patternsmgetnames
List column names by classnames_by_class
Convert one-hot encoded matrix to factorone_hot2factor
Get the outcome as a vectoroutcome
Get the name of the last columnoutcome_name
Manhattan plotplot_manhattan plot_manhattan.MassGLM
Plot ROC curveplot_roc
Plot True vs. Predicted Valuesplot_true_pred
Plot Variable Importanceplot_varimp
Plot MassGLM using volcano plotplot.MassGLM
Preprocess Datapreprocess preprocess.class_tabular.Preprocessor preprocess.class_tabular.PreprocessorConfig
Get preprocessed data from 'Preprocessor'.preprocessed
Present rtemis objectpresent
Preview colorpreviewcolor
Read tabular data from a variety of formatsread
Read 'SuperConfig' from TOML fileread_config
Regression Metricsregression_metrics
Resample dataresample
Random Normal Matrixrnormmat
rtemis Color Systemrtemis_colors
Get rtemis version and system infortversion
Random Uniform Matrixrunifmat
Set the rtemis message sinkset_msg_sink
Move outcome to last columnset_outcome
Symmetric Set Differencesetdiffsym
Setup CART Hyperparameterssetup_CART
Setup CMeansConfigsetup_CMeans
Setup DBSCANConfigsetup_DBSCAN
Setup Execution Configurationsetup_ExecutionConfig
Setup GAM Hyperparameterssetup_GAM
Setup GLM Hyperparameterssetup_GLM
Setup GLMNET Hyperparameterssetup_GLMNET
Setup Grid Search Configsetup_GridSearch
Setup HardCLConfigsetup_HardCL
setup_ICAsetup_ICA
Setup Isomap config.setup_Isomap
Setup Isotonic Hyperparameterssetup_Isotonic
Setup KMeansConfigsetup_KMeans
Setup LightCART Hyperparameterssetup_LightCART
Setup LightGBM Hyperparameterssetup_LightGBM
Setup LightRF Hyperparameterssetup_LightRF
Setup LightRuleFit Hyperparameterssetup_LightRuleFit
Setup LinearSVM Hyperparameterssetup_LinearSVM
Setup NeuralGasConfigsetup_NeuralGas
Setup NMF config.setup_NMF
Setup PCA config.setup_PCA
Setup Preprocessorsetup_Preprocessor
Setup RadialSVM Hyperparameterssetup_RadialSVM
Setup Ranger Hyperparameterssetup_Ranger
Setup Resamplersetup_Resampler
Setup SuperConfigsetup_SuperConfig
Setup SuperConfigLivesetup_SuperConfigLive
Setup TabNet Hyperparameterssetup_TabNet
Setup tSNE config.setup_tSNE
Setup UMAP config.setup_UMAP
Size of objectsize
Tabulate column attributestable_column_attr
Themes for draw_* functionstheme_black theme_blackgrid theme_blackigrid theme_darkgray theme_darkgraygrid theme_darkgrayigrid theme_lightgraygrid theme_mediumgraygrid theme_white theme_whitegrid theme_whiteigrid
Train Supervised Learning Modelstrain
Get protein sequence from UniProtuniprot_get
Run code with a temporary message sinkwith_msg_sink
Write to TOML filewrite_toml
Example longitudinal datasetxt_example
Describe longitudinal datasetxtdescribe