predictive analytics

Wednesday, December 5, 2018 - 10:30am - 11:30am
Hamsa Bastani (Wharton School of the University of Pennsylvania)
Machine learning is increasingly used to inform consequential decisions. Yet, these predictive models have been found to exhibit unexpected defects when trained on real-world observational data, which are plagued with confounders and biases. Thus, it is critical to involve domain experts in an interactive process of developing predictive models; interpretability offers a promising way to facilitate this interaction.
Wednesday, October 3, 2018 - 2:00pm - 2:45pm
Hamsa Bastani (Wharton School of the University of Pennsylvania)
Predictive analytics is increasingly used to guide decision-making in many applications. However, in practice, we often have limited data on the true outcome that we wish to predict, but copious data on an intermediate or proxy outcome. Practitioners often train predictive models on proxies since it achieves more accurate predictions.
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