Package: stressor 0.2.0

stressor: Algorithms for Testing Models under Stress

Traditional model evaluation metrics fail to capture model performance under less than ideal conditions. This package employs techniques to evaluate models "under-stress". This includes testing models' extrapolation ability, or testing accuracy on specific sub-samples of the overall model space. Details describing stress-testing methods in this package are provided in Haycock (2023) <doi:10.26076/2am5-9f67>. The other primary contribution of this package is provided to R users access to the 'Python' library 'PyCaret' <https://pycaret.org/> for quick and easy access to auto-tuned machine learning models.

Authors:Sam Haycock [aut, cre], Brennan Bean [aut], Utah State University [cph, fnd], Thermo Fisher Scientific Inc. [fnd]

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17 exports 0.23 score 26 dependencies 6 scripts 908 downloads

Last updated 5 months agofrom:d00feeb9b6. Checks:OK: 7. Indexed: yes.

Exports:create_groupscreate_virtualenvcvcv_clusterdata_gen_asymdata_gen_lmdata_gen_sinedist_centmlm_classificationmlm_refitmlm_regressorpython_availreg_asymreg_sinescoresplit_data_probthinning

Dependencies:clidplyrfansigenericsglueherejsonlitelatticelifecyclemagrittrMatrixpillarpkgconfigpngR6rappdirsRcppRcppTOMLreticulaterlangrprojroottibbletidyselectutf8vctrswithr