Package: familiar 1.5.0
familiar: End-to-End Automated Machine Learning and Model Evaluation
Single unified interface for end-to-end modelling of regression, categorical and time-to-event (survival) outcomes. Models created using familiar are self-containing, and their use does not require additional information such as baseline survival, feature clustering, or feature transformation and normalisation parameters. Model performance, calibration, risk group stratification, (permutation) variable importance, individual conditional expectation, partial dependence, and more, are assessed automatically as part of the evaluation process and exported in tabular format and plotted, and may also be computed manually using export and plot functions. Where possible, metrics and values obtained during the evaluation process come with confidence intervals.
Authors:
familiar_1.5.0.tar.gz
familiar_1.5.0.zip(r-4.5)familiar_1.5.0.zip(r-4.4)familiar_1.5.0.zip(r-4.3)
familiar_1.5.0.tgz(r-4.4-any)familiar_1.5.0.tgz(r-4.3-any)
familiar_1.5.0.tar.gz(r-4.5-noble)familiar_1.5.0.tar.gz(r-4.4-noble)
familiar_1.5.0.tgz(r-4.4-emscripten)familiar_1.5.0.tgz(r-4.3-emscripten)
familiar.pdf |familiar.html✨
familiar/json (API)
NEWS
| # Install 'familiar' in R: |
| install.packages('familiar', repos = c('https://alexzwanenburg.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alexzwanenburg/familiar/issues
aiexplainable-aimachine-learningsurvival-analysistabular-data
Last updated 2 months agofrom:7fe6fb005d. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 22 2024 |
| R-4.5-win | WARNING | Nov 22 2024 |
| R-4.5-linux | WARNING | Nov 22 2024 |
| R-4.4-win | WARNING | Nov 22 2024 |
| R-4.4-mac | WARNING | Nov 22 2024 |
| R-4.3-win | WARNING | Nov 22 2024 |
| R-4.3-mac | WARNING | Nov 22 2024 |
Exports:aggregate_vimp_tableas_data_objectas_familiar_collectionas_familiar_dataas_familiar_ensemblecoefexport_allexport_auc_dataexport_calibration_dataexport_calibration_infoexport_confusion_matrix_dataexport_decision_curve_analysis_dataexport_feature_expressionsexport_feature_similarityexport_fs_vimpexport_hyperparametersexport_ice_dataexport_model_performanceexport_model_vimpexport_partial_dependence_dataexport_permutation_vimpexport_prediction_dataexport_risk_stratification_dataexport_risk_stratification_infoexport_sample_similarityexport_univariate_analysis_dataget_class_namesget_data_set_namesget_feature_namesget_fs_method_namesget_learner_namesget_risk_group_namesget_vimp_tableget_xml_configplot_auc_precision_recall_curveplot_auc_roc_curveplot_calibration_dataplot_confusion_matrixplot_decision_curveplot_feature_selection_occurrenceplot_feature_selection_variable_importanceplot_feature_similarityplot_iceplot_kaplan_meierplot_model_performanceplot_model_signature_occurrenceplot_model_signature_variable_importanceplot_permutation_variable_importanceplot_sample_clusteringplot_univariate_importanceplot_variable_importanceprecompute_data_assignmentprecompute_feature_infoprecompute_vimppredictset_class_namesset_data_set_namesset_feature_namesset_fs_method_namesset_learner_namesset_risk_group_namessummarysummon_familiartheme_familiartrain_familiarupdate_model_dir_pathupdate_objectvcovwaiver
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregate variable importance from multiple variable importance objects. | aggregate_vimp_table aggregate_vimp_table,character-method aggregate_vimp_table,experimentData-method aggregate_vimp_table,list-method aggregate_vimp_table,NULL-method aggregate_vimp_table,vimpTable-method |
| Creates a valid data object from input data. | as_data_object as_data_object,ANY-method as_data_object,data.table-method as_data_object,dataObject-method |
| Conversion to familiarCollection object. | as_familiar_collection as_familiar_collection,ANY-method as_familiar_collection,character-method as_familiar_collection,familiarCollection-method as_familiar_collection,familiarData-method as_familiar_collection,familiarEnsemble-method as_familiar_collection,familiarModel-method as_familiar_collection,list-method |
| Conversion to familiarData object. | as_familiar_data as_familiar_data,ANY-method as_familiar_data,character-method as_familiar_data,familiarData-method as_familiar_data,familiarEnsemble-method as_familiar_data,familiarModel-method as_familiar_data,list-method |
| Conversion to familiarEnsemble object. | as_familiar_ensemble as_familiar_ensemble,ANY-method as_familiar_ensemble,character-method as_familiar_ensemble,familiarEnsemble-method as_familiar_ensemble,familiarModel-method as_familiar_ensemble,list-method |
| Extract model coefficients | coef coef,familiarModel-method |
| Data object | dataObject-class |
| Experiment data | experimentData-class |
| Extract and export all data. | export_all export_all,ANY-method export_all,familiarCollection-method |
| Extract and export ROC and Precision-Recall curves. | export_auc_data export_auc_data,ANY-method export_auc_data,familiarCollection-method |
| Extract and export calibration and goodness-of-fit tests. | export_calibration_data export_calibration_data,ANY-method export_calibration_data,familiarCollection-method |
| Extract and export calibration information. | export_calibration_info export_calibration_info,ANY-method export_calibration_info,familiarCollection-method |
| Extract and export confusion matrices. | export_confusion_matrix_data export_confusion_matrix_data,ANY-method export_confusion_matrix_data,familiarCollection-method |
| Extract and export decision curve analysis data. | export_decision_curve_analysis_data export_decision_curve_analysis_data,ANY-method export_decision_curve_analysis_data,familiarCollection-method |
| Extract and export feature expressions. | export_feature_expressions export_feature_expressions,ANY-method export_feature_expressions,familiarCollection-method |
| Extract and export mutual correlation between features. | export_feature_similarity export_feature_similarity,ANY-method export_feature_similarity,familiarCollection-method |
| Extract and export feature selection variable importance. | export_fs_vimp export_fs_vimp,ANY-method export_fs_vimp,familiarCollection-method |
| Extract and export model hyperparameters. | export_hyperparameters export_hyperparameters,ANY-method export_hyperparameters,familiarCollection-method |
| Extract and export individual conditional expectation data. | export_ice_data export_ice_data,ANY-method export_ice_data,familiarCollection-method |
| Extract and export metrics for model performance. | export_model_performance export_model_performance,ANY-method export_model_performance,familiarCollection-method |
| Extract and export model-based variable importance. | export_model_vimp export_model_vimp,ANY-method export_model_vimp,familiarCollection-method |
| Extract and export partial dependence data. | export_partial_dependence_data export_partial_dependence_data,ANY-method export_partial_dependence_data,familiarCollection-method |
| Extract and export permutation variable importance. | export_permutation_vimp export_permutation_vimp,ANY-method export_permutation_vimp,familiarCollection-method |
| Extract and export predicted values. | export_prediction_data export_prediction_data,ANY-method export_prediction_data,familiarCollection-method |
| Extract and export sample risk group stratification and associated tests. | export_risk_stratification_data export_risk_stratification_data,ANY-method export_risk_stratification_data,familiarCollection-method |
| Extract and export cut-off values for risk group stratification. | export_risk_stratification_info export_risk_stratification_info,ANY-method export_risk_stratification_info,familiarCollection-method |
| Extract and export mutual correlation between features. | export_sample_similarity export_sample_similarity,ANY-method export_sample_similarity,familiarCollection-method |
| Extract and export univariate analysis data of features. | export_univariate_analysis_data export_univariate_analysis_data,ANY-method export_univariate_analysis_data,familiarCollection-method |
| familiar: Fully Automated Machine Learning with Interpretable Analysis of Results | familiar-package familiar |
| Collection of familiar data. | familiarCollection-class |
| Dataset obtained after evaluating models on a dataset. | familiarData-class |
| Data container for evaluation data. | familiarDataElement-class |
| Ensemble of familiar models. | familiarEnsemble-class |
| Hyperparameter learner. | familiarHyperparameterLearner-class |
| Model performance metric. | familiarMetric-class |
| Familiar model. | familiarModel-class |
| Novelty detector. | familiarNoveltyDetector-class |
| Variable importance method object. | familiarVimpMethod-class |
| Feature information object. | featureInfo-class |
| Feature information parameters object. | featureInfoParameters-class |
| Get outcome class labels | get_class_names get_class_names,familiarCollection-method |
| Get current name of datasets | get_data_set_names get_data_set_names,familiarCollection-method |
| Get current feature labels | get_feature_names get_feature_names,familiarCollection-method |
| Get current feature selection method name labels | get_fs_method_names get_fs_method_names,familiarCollection-method |
| Get current learner name labels | get_learner_names get_learner_names,familiarCollection-method |
| Get current risk group labels | get_risk_group_names get_risk_group_names,familiarCollection-method |
| Extract variable importance table. | get_vimp_table get_vimp_table,character-method get_vimp_table,experimentData-method get_vimp_table,familiarModel-method get_vimp_table,list-method get_vimp_table,NULL-method get_vimp_table,vimpTable-method |
| Create an empty xml configuration file | get_xml_config |
| Outcome information object. | outcomeInfo-class |
| Plot the precision-recall curve. | plot_auc_precision_recall_curve plot_auc_precision_recall_curve,ANY-method plot_auc_precision_recall_curve,familiarCollection-method |
| Plot the receiver operating characteristic curve. | plot_auc_roc_curve plot_auc_roc_curve,ANY-method plot_auc_roc_curve,familiarCollection-method |
| Plot calibration figures. | plot_calibration_data plot_calibration_data,ANY-method plot_calibration_data,familiarCollection-method |
| Plot confusion matrix. | plot_confusion_matrix plot_confusion_matrix,ANY-method plot_confusion_matrix,familiarCollection-method |
| Plot decision curves. | plot_decision_curve plot_decision_curve,ANY-method plot_decision_curve,familiarCollection-method |
| Plot heatmaps for pairwise similarity between features. | plot_feature_similarity plot_feature_similarity,ANY-method plot_feature_similarity,familiarCollection-method |
| Plot individual conditional expectation plots. | plot_ice plot_ice,ANY-method plot_ice,familiarCollection-method |
| Plot Kaplan-Meier survival curves. | plot_kaplan_meier plot_kaplan_meier,ANY-method plot_kaplan_meier,familiarCollection-method |
| Plot model performance. | plot_model_performance plot_model_performance,ANY-method plot_model_performance,familiarCollection-method |
| Plot partial dependence. | plot_pd plot_pd,ANY-method |
| Plot permutation variable importance. | plot_permutation_variable_importance plot_permutation_variable_importance,ANY-method plot_permutation_variable_importance,familiarCollection-method |
| Plot heatmaps for pairwise similarity between features. | plot_sample_clustering plot_sample_clustering,ANY-method plot_sample_clustering,familiarCollection-method |
| Plot univariate importance. | plot_univariate_importance plot_univariate_importance,ANY-method plot_univariate_importance,familiarCollection-method |
| Plot variable importance scores of features during feature selection or after training a model. | plot_feature_selection_occurrence plot_feature_selection_variable_importance plot_model_signature_occurrence plot_model_signature_variable_importance plot_variable_importance plot_variable_importance,ANY-method plot_variable_importance,familiarCollection-method |
| Pre-compute data assignment | precompute_data_assignment |
| Pre-compute feature information | precompute_feature_info |
| Pre-compute variable importance | precompute_vimp |
| Model predictions for familiar models and model ensembles | predict predict,character-method predict,familiarEnsemble-method predict,familiarModel-method predict,familiarNoveltyDetector-method predict,list-method |
| Rename outcome classes for plotting and export | set_class_names set_class_names,familiarCollection-method |
| Name datasets for plotting and export | set_data_set_names set_data_set_names,familiarCollection-method |
| Rename features for plotting and export | set_feature_names set_feature_names,familiarCollection-method |
| Rename feature selection methods for plotting and export | set_fs_method_names set_fs_method_names,familiarCollection-method |
| Rename learners for plotting and export | set_learner_names set_learner_names,familiarCollection-method |
| Rename risk groups for plotting and export | set_risk_group_names set_risk_group_names,familiarCollection-method |
| Model summaries | summary summary,familiarModel-method |
| Perform end-to-end machine learning and data analysis | summon_familiar |
| Familiar ggplot2 theme | theme_familiar |
| Create models using end-to-end machine learning | train_familiar |
| Updates model directory path for ensemble objects. | update_model_dir_path update_model_dir_path,ANY-method update_model_dir_path,familiarEnsemble-method |
| Update familiar S4 objects to the most recent version. | update_object update_object,ANY-method update_object,experimentData-method update_object,familiarCollection-method update_object,familiarData-method update_object,familiarEnsemble-method update_object,familiarModel-method update_object,familiarNoveltyDetector-method update_object,featureInfo-method update_object,featureInfoParametersTransformationPowerTransform-method update_object,list-method update_object,vimpTable-method |
| Calculate variance-covariance matrix for a model | vcov vcov,familiarModel-method |
| Variable importance table | vimpTable-class |
| Create a waiver object | waiver |
