Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparing Strategies for Post-Hoc Explanations in Machine Learning Models Subject The topic of the resource ELI5; Explainable AI; Interpretability; LIME; SHAP Description An account of the resource Most of the machine learning models act as black boxes, and hence, the need for interpreting them is rising. There are multiple approaches to understand the outcomes of a model. But in order to be able to trust the interpretations, there is a need to have a closer look at these approaches. This project compared three such frameworksELI5, LIME and SHAP. ELI5 and LIME follow the same approach toward interpreting the outcomes of machine learning algorithms by building an explainable model in the vicinity of the datapoint that needs to be explained, whereas SHAP works with Shapley values, a game theory approach toward assigning feature attribution. LIME outputs an R-squared value along with its feature attribution reports which help in quantifying the trust one must have in those interpretations. The R-squared value for surrogate models within different machine learning models varies. SHAP trades-off accuracy with time (theoretically). Assigning SHAP values to features is a time and computationally consuming task, and hence, it might require sampling beforehand. SHAP triumphs over LIME with respect to optimization of different kinds of machine learning models as it has explainers for different types of machine learning models, and LIME has one generic explainer for all model types. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Vij A.; Nanjundan P. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-68, pp. 585-592. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-16-1866-6_41" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-16-1866-6_41</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112011742&amp;doi=10.1007%2F978-981-16-1866-6_41&amp;partnerID=40&amp;md5=2b77e6d865f288e945e54034ab5bbec3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112011742&amp;doi=10.1007%2f978-981-16-1866-6_41&amp;partnerID=40&amp;md5=2b77e6d865f288e945e54034ab5bbec3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23674512 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vij A., Christ (Deemed To Be University), Lavasa, India; Nanjundan P., Christ (Deemed To Be University), Lavasa, India