Explanations of model predictions with live and breakDown packages

Greedy function approximation: A gradient boosting machine

J. H. Friedman · 2001

Earlier work this paper cites.

Opening the black box - data driven visualization of neural networks

F. Y. Tzeng and K. L. Ma · 2005

Earlier work this paper cites.

Explaining classifications for individual instances

M. Robnik-Šikonja and I. Kononenko · 2007

Earlier work this paper cites.

Conditional variable importance for random forests

C. Strobl, A.-L. Boulesteix, T. Kneib, T. Augustin, and A. Zeileis · 2008

Earlier work this paper cites.

Modeling wine preferences by data mining from physicochemical properties

P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis · 2009

Earlier work this paper cites.

Regularization paths for generalized linear models via coordinate descent

J. Friedman, T. Hastie, and R. Tibshirani · 2010

Earlier work this paper cites.

Regularization paths for cox’s proportional hazards model via coordinate descent

N. Simon, J. Friedman, T. Hastie, and R. Tibshirani · 2011

Earlier work this paper cites.

A general method for visualizing and explaining black-box regression models

E. Štrumbelj and I. Kononenko · 2011

Earlier work this paper cites.

Peeking Inside the Black Box: Visualizing Statistical Learning with Plots of Individual Conditional Expectation

A. Goldstein, A. Kapelner, J. Bleich, and E. Pitkin · 2013

Cited alongside, same era.

Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation

A. Goldstein, A. Kapelner, J. Bleich, and E. Pitkin · 2014

Cited alongside, same era.

Visualizing and Understanding Convolutional Networks , page 818–833

M. D. Zeiler and R. Fergus · 2014

Cited alongside, same era.

Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models

D. W. Apley · 2016

Cited alongside, same era.

mlr: Machine learning in r

B. Bischl, M. Lang, L. Kotthoff, J. Schiffner, J. Richter, E. Studerus, G. Casalicchio, and Z. M. Jones · 2016

Cited alongside, same era.

Anthony Goldbloom gives you the secret to winning Kaggle competitions , 2016

data.table: Extension of ‘data.frame‘ , 2017

M. Dowle and A. Srinivasan · 2017

Later among the works it cites.

pdp: An R Package for Constructing Partial Dependence Plots

B. M. Greenwell · 2017

Later among the works it cites.

forestmodel: Forest Plots from Regression Models , 2017

N. Kennedy · 2017

Later among the works it cites.

A unified approach to interpreting model predictions

S. Lundberg and S.-I. Lee · 2017

Later among the works it cites.

lime: Local Interpretable Model-Agnostic Explanations , 2017

T. L. Pedersen and M. Benesty · 2017

Later among the works it cites.

MAGIX: Model Agnostic Globally Interpretable Explanations

N. Puri, P. Gupta, P. Agarwal, S. Verma, and B. Krishnamurthy · 2017

Later among the works it cites.