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Interpretability: Difference between revisions
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(Created page with "{{see also|Machine learning terms}} ===Interpretability in Machine Learning== Interpretability in machine learning refers to the process of comprehending and explaining the actions taken by a model. It plays an essential role in developing these models, particularly in fields such as healthcare, finance and criminal justice where decisions made by these algorithms may have far-reaching repercussions for individuals and society at large. Interpretability is the goal of i...") |
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{{see also|Machine learning terms}} | {{see also|Machine learning terms}} | ||
==Interpretability in Machine Learning== | |||
Interpretability in machine learning refers to the process of comprehending and explaining the actions taken by a model. It plays an essential role in developing these models, particularly in fields such as healthcare, finance and criminal justice where decisions made by these algorithms may have far-reaching repercussions for individuals and society at large. | Interpretability in machine learning refers to the process of comprehending and explaining the actions taken by a model. It plays an essential role in developing these models, particularly in fields such as healthcare, finance and criminal justice where decisions made by these algorithms may have far-reaching repercussions for individuals and society at large. | ||