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	Podcast:		Linear Digressions
	Episode:		Model Interpretation (and Trust Issues)
	Category:		Technology
	Duration:		00:16:57
	Publish Date:		2016-04-24 19:45:04
	Description:		Machine learning algorithms can be black boxes--inputs go in, outputs come out, and what happens in the middle is anybody's guess. But understanding how a model arrives at an answer is critical for interpreting the model, and for knowing if it's doing something reasonable (one could even say... trustworthy). We'll talk about a new algorithm called LIME that seeks to make any model more understandable and interpretable. Relevant Links: http://arxiv.org/abs/1602.04938 https://github.com/marcotcr/lime/tree/master/lime
	Total Play:		0

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