DSC/e Lecture Marko Robnik-Sikonja: Explaining individual predictions with...

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Luna building - Corona room

TU/e

De Lampendriessen 31

5612 AZ Eindhoven

Netherlands

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DSC/e Lecture Series

Speaker:
Marko Robnik-Sikonja, University at Buffalo

Title:
Explaining individual predictions with perturbations of inputs

Doors open at 12:00 h.



Current research into algorithmic explanation methods for predictive models can be divided into two main approaches: gradient-based approaches limited to neural networks, and more general perturbation-based approaches which can be used with arbitrary prediction models. We present an overview of perturbation-based approaches, with focus on popular methods (EXPLAIN, IME, LIME). These methods support explanation of individual predictions but can also visualize the model as a whole. The EXPLAIN method perturbs one input at a time, IME uses game theory based sampling to control interactions between inputs, while LIME perturbs instances in the locality of explained instances. We describe their working principles, how they handle computational complexity, their visualizations as well as their advantages and disadvantages. We illustrate issues and challenges in applying the explanation methodology on practical use cases from medicine and B2B sales forecasting in a company.

Biography Marko Robnik-Sikonja




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Datum en tijd

Locatie

Luna building - Corona room

TU/e

De Lampendriessen 31

5612 AZ Eindhoven

Netherlands

Kaart bekijken

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