Interpreting Tree Ensembles with inTrees

L. Breiman, J. Friedman, R. Olshen, C. Stone., Classification and Regression Trees, Wadsworth, Belmont, MA, 1984

1984

Earlier work this paper cites.

R. Agrawal, R. Srikant, et al., Fast algorithms for mining association rules, in: Proc. 20th int. conf. very large data bases, VLDB, volume 1215, pp. 487–499

1994

Earlier work this paper cites.

C. Blake, C. Merz, UCI repository of machine learning databases (1998)

1998

Earlier work this paper cites.

B. Liu, W. Hsu, Y. Ma, Integrating classification and association rule mining, in: Proceeding of the 1998 International Conference on Knowledge Discovery and Data Mining, ACM, 1998, pp. 80–86

1998

Earlier work this paper cites.

L. Breiman, Random forests, Machine learning 45 (2001) 5–32

2001

Earlier work this paper cites.

J.H. Friedman, Greedy function approximation: a gradient boosting machine, Annals of Statistics (2001) 1189–1232

2001

Cited alongside, same era.

A. Liaw, M. Wiener, Classification and regression by randomforest, R news 2 (2002) 18–22

2002

Cited alongside, same era.

G. Ridgeway, Generalized boosted regression models, Documentation on the R Package ‘gbm’, version 1· 5 7 (2006)

2006

Cited alongside, same era.

M. Hahsler, B. Grün, K. Hornik, Introduction to arules–mining association rules and frequent item sets, SIGKDD EXPLORATIONS (2007)

2007

Cited alongside, same era.

J.H. Friedman, B.E. Popescu, Predictive learning via rule ensembles, The Annals of Applied Statistics (2008) 916–954

2008

Cited alongside, same era.

T.M. Therneau, B. Atkinson, B. Ripley, rpart: Recursive partitioning, R package version 3 (2010)

Original

2010

Later among the works it cites.

S. Kaufman, S. Rosset, C. Perlich, O. Stitelman, Leakage in data mining: Formulation, detection, and avoidance, ACM Transactions on Knowledge Discovery from Data (TKDD) 6 (2012) 15

2012

Later among the works it cites.

H. Deng, G. Runger, Gene selection with guided regularized random forest, Pattern Recognition 46 (2013) 3483–3489

2013

Later among the works it cites.

H. Deng, G. Runger, E. Tuv, W. Bannister, Cbc: An associative classifier with a small number of rules, Decision Support Systems 59 (2014) 163–170

2014

Closest in time.