Introduction to Machine Learning Interpretability /
نام عام مواد
[Book]
نام نخستين پديدآور
Patrick Hall. Navdeep Gill.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
[Place of publication not identified]
نام ناشر، پخش کننده و غيره
O'Reilly Media, Inc.,
تاریخ نشرو بخش و غیره
2018.
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource
يادداشت کلی
متن يادداشت
Title from content provider.
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Innovation and competition are driving analysts and data scientists toward increasingly complex predictive modeling and machine learning algorithms. This complexity makes these models accurate but also makes their predictions difficult to understand. When accuracy outpaces interpretability, human trust suffers, affecting business adoption, regulatory oversight, and model documentation. Banking, insurance, and healthcare in particular require predictive models that are interpretable. In this ebook, Patrick Hall and Navdeep Gill from H2O.ai thoroughly introduce the idea of machine learning interpretability and examine a set of machine learning techniques, algorithms, and models to help data scientists improve the accuracy of their predictive models while maintaining interpretability. Learn how machine learning and predictive modeling are applied in practice Understand social and commercial motivations for machine learning interpretability, fairness, accountability, and transparency Explore the differences between linear models and more accurate machine learning models Get a definition of interpretability and learn about the groups leading interpretability research Examine a taxonomy for classifying and describing interpretable machine learning approaches Learn several practical techniques for data visualization, training interpretable machine learning models, and generating explanations for complex model predictions Explore automated approaches for testing model interpretability.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
R (Computer program language)
موضوع مستند نشده
Statistics-- Data processing.
موضوع مستند نشده
R (Computer program language)
موضوع مستند نشده
Statistics-- Data processing.
رده بندی ديویی
شماره
[
E
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نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )