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Prediction accuracy and model explainability are the two most important objectives when developing machine learning algorithms to solve real-world problems.
Projection pursuit regression
Jerome H Friedman and Werner Stuetzle · 1981
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Jeng-Neng Hwang, Shyh-Rong Lay, Martin Maechler, R Douglas Martin, and Jim Schimert · 1994
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Greedy function approximation: a gradient boosting machine
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Generalized additive and index models with shape constraints
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Why should I trust you? Explaining the predictions of any classifier
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David Gunning · 2017
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What are we learning about artificial intelligence in financial services?
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