Explanation and reliability of prediction models: the case of breast cancer recurrence |
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Authors: | Erik ?trumbelj Zoran Bosni? Igor Kononenko Branko Zakotnik Cvetka Gra?i? Kuhar |
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Affiliation: | 1. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia 2. Institute of Oncology, Ljubljana, Slovenia
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Abstract: | In this paper, we describe the first practical application of two methods, which bridge the gap between the non-expert user
and machine learning models. The first is a method for explaining classifiers’ predictions, which provides the user with additional
information about the decision-making process of a classifier. The second is a reliability estimation methodology for regression
predictions, which helps the users to decide to what extent to trust a particular prediction. Both methods are successfully
applied to a novel breast cancer recurrence prediction data set and the results are evaluated by expert oncologists. |
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