API

This is the full API documentation of the research-learn package.

rlearn.model_selection: Search the model space

The rlearn.model_selection module includes the model and parameter search methods.

ModelSearchCV(estimators, param_grids[, …])

Exhaustive search over specified parameter values for a collection of estimators.

rlearn.experiment: Tools to run machine learning experiments

ImbalancedClassificationExperiment

rlearn.reporting: Tools to report results of experiments

The rlearn.tools module includes various functions to analyze and visualize the results of model search and experiments on multiple datasets.

report_model_search_results(model_search_cv)	Generate a model search report of results.
summarize_imbalanced_binary_datasets(datasets)	Create a summary of imbalanced datasets.
apply_friedman_test(imbalanced_experiment[, …])	Apply the Friedman test across datasets for every combination of classifiers and metrics.
apply_holms_test(imbalanced_experiment[, …])	Use the Holm’s method to adjust the p-values of a paired difference t-test for every combination of classifiers and metrics using a control oversampler.