Learn R Programming

sbrl (version 1.4)

Scalable Bayesian Rule Lists Model

Description

An efficient implementation of Scalable Bayesian Rule Lists Algorithm, a competitor algorithm for decision tree algorithms; see Hongyu Yang, Cynthia Rudin, Margo Seltzer (2017) . It builds from pre-mined association rules and have a logical structure identical to a decision list or one-sided decision tree. Fully optimized over rule lists, this algorithm strikes practical balance between accuracy, interpretability, and computational speed.

Copy Link

Version

Install

install.packages('sbrl')

Monthly Downloads

139

Version

1.4

License

GPL (>= 2)

Maintainer

Hongyu Yang

Last Published

April 8th, 2024

Functions in sbrl (1.4)

get_data_feature_mat

GET BINARY MATRIX REPRESENTATION OF THE DATA-FEATURE RELAITONSHIP
sbrl-package

SCALABLE BAYESIAN RULE LISTS
predict.sbrl

PREDICT THE POSITIVE PROBABILITY FOR THE OBSERVATIONS
tictactoe

SHUFFLED TIC-TAC-TOE-ENDGAME DATASET
print.sbrl

INTERPRETABLE VERSION OF A SBRL MODEL
sbrl

fit the scalable bayesian rule lists model