Turning prediction tools into decision tools

Published

Conference Paper

© Springer International Publishing Switzerland 2015. Arguably, the main stumbling block in getting machine learning algorithms used in practice is the fact that people do not trust them. There could be many reasons for this, for instance, perhaps the models are not sparse or transparent, or perhaps the models are not able to be customized to the user’s specifications as to what a decision tool should look like. I will discuss some recent work from the Prediction Analysis Lab on how to build machine learning models that have helpful decision-making properties. I will show how these models are applied to problems in healthcare and criminology.

Duke Authors

Cited Authors

  • Rudin, C

Published Date

  • January 1, 2015

Published In

Volume / Issue

  • 9355 /

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 13 (ISBN-13)

  • 9783319244853

Citation Source

  • Scopus