subpick | R Documentation |
submodular
pick algorithm PP SP-LIME
Pick several data containing various information for each final node for PPTreereg
submodular
Pick (SP-LIME
) was developed (Ribeiro et al., 2016) to selects
representative data with important information to determine the
reliability of model based on the LIME
algorithm.
In order to extract data for each final node in the PPTreereg
model,
PP SP-LIME
was proposed based on SP-LIME
.
subpick(data_long, final.leaf, obsnum = 5)
data_long |
|
final.leaf |
location of final leaf |
obsnum |
The number of budgets (instance to be selected). Default value is 1. |
Observation names and their original values as data
Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. "" Why should i trust you?" Explaining the predictions of any classifier." Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. 2016. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1145/2939672.2939778")} https://github.com/marcotcr/lime/blob/master/lime/submodular_pick.py
data("dataXY")
Model <- PPTreereg(Y~., data = dataXY, DEPTH = 2)
shap_long=ppshapr_prep(Model,final.rule =3,method="simple")
subpick(shap_long,final.leaf = 1, obsnum = 5)
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