_intelligible-machine-learning-models-for-health-care-richard-caruana.jpg "Intelligible Machine Learning Models for Health Care Richard Caruana from phd machine learning cmu Video Screenshot Preview")
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⏲ Duration: 38 min 77 sec
✓ Published: 25-Apr-2015
✓ Published: 25-Apr-2015
Description:
In machine learning, often a tradeoff must be made between accuracy and intelligibility: the most accurate models usually are not very intelligible (e.g., random forests, boosted trees, and neural nets), and the most intelligible models usually are less accurate (e.g., linear or logistic regression). This tradeoff often limits the accuracy of models that can be applied in mission-critical applications such as healthcare where being able to understand, validate, edit, and trust a learned model is
In machine learning, often a tradeoff must be made between accuracy and intelligibility: the most accurate models usually are not very intelligible (e.g., random forests, boosted trees, and neural nets), and the most intelligible models usually are less accurate (e.g., linear or logistic regression). This tradeoff often limits the accuracy of models that can be applied in mission-critical applications such as healthcare where being able to understand, validate, edit, and trust a learned model is
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