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Running head: EXPLAINABLE MACHINE LEARNING FOR CREDIT LENDING1Explainable Machine Learning for Credit Lending CMPE257 Machine Learning Term Project Praveen Manifold Kai Kwan Poor Courtney Nguyen San
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What is explainable machine learning for?
Explainable machine learning is intended to enhance the transparency and understanding of machine learning models, making it easier for users to comprehend how decisions are made by these models.
Who is required to file explainable machine learning for?
Organizations and individuals developing or deploying machine learning models that significantly impact stakeholders, particularly in regulated industries such as finance and healthcare, are required to file explainable machine learning reports.
How to fill out explainable machine learning for?
To fill out an explainable machine learning report, one must provide details about the model's architecture, data used for training and validation, evaluation metrics, and mechanisms for interpreting the model's decisions.
What information must be reported on explainable machine learning for?
The report must include the model's implementation details, performance metrics, potential biases, interpretability methods used, and examples of how decisions are made by the model.
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