2014, Data mining, Knowledge Discovery and Testing

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

AUGUST 1, 2021

Joint training, for example, adds an additional “explanation task” to the original problem and trains the system to solve the two “jointly” (see Bahdanau, 2014). After forming the X and y variables, we split the data into training and test sets. Conference on Knowledge Discovery and Data Mining, pp.

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Explaining black-box models using attribute importance, PDPs, and LIME

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