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With the growing adoption of machine learning techniques, there is a surge of research interest towards making machine learning systems more transparent and interpretable.
Classification and regression trees
L. Breiman, J. Friedman, C. J. Stone, and R. A. Olshen · 1984
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Density estimation for statistics and data analysis
B. W. Silverman · 1986
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Generating production rules from decision trees
J. R. Quinlan · 1987
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Using the adap learning algorithm to forecast the onset of diabetes mellitus
J. W. Smith, J. Everhart, W. Dickson, W. Knowler, and R. Johannes · 1988
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From decision tables to expert system shells
J. Vanthienen and G. Wets · 1994
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Learning with decision lists of data-dependent features
M. Marchand and M. Sokolova · 2005
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Opening the black box-data driven visualization of neural networks
F.-Y. Tzeng and K.-L. Ma · 2005
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Beautiful Evidence
E. R. Tufte · 2006
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User-oriented assessment of classification model understandability
H. Allahyari and N. Lavesson · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Cited alongside, same era.
BaobabView: Interactive construction and analysis of decision trees
S. van den Elzen and J. J. van Wijk · 2011
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Deep inside convolutional networks: Visualising image classification models and saliency maps
K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
Cited alongside, same era.
European union regulations on algorithmic decision-making and a ”right to explanation”
B. Goodman and S. Flaxman · 2017
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A workflow for visual diagnostics of binary classifiers using instance-level explanations
J. Krause, A. Dasgupta, J. Swartz, Y. Aphinyanaphongs, and E. Bertini · 2017
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Towards better analysis of machine learning models: A visual analytics perspective
S. Liu, X. Wang, M. Liu, and J. Zhu · 2017
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Understanding hidden memories of recurrent neural networks
Y. Ming, S. Cao, R. Zhang, Z. Li, Y. Chen, Y. Song, and H. Qu · 2017
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Visualizing the hidden activity of artificial neural networks
P. E. Rauber, S. G. Fadel, A. X. Falcão, and A. C. Telea · 2017
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Scalable Bayesian rule lists
H. Yang, C. Rudin, and M. Seltzer · 2017
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M. D. Zeiler and R. Fergus · 2014
Cited alongside, same era.
Falling Rule Lists
F. Wang and C. Rudin · 2015
Cited alongside, same era.
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