plot_importance

object

Show top_n variables only, default=NULL (show all)

top_n

Additional arguments (currently ignored).

Importance is currently based on the PRISM filter model. For elastic net (filter_glmnet).
variables with non-zero coefficients are shown. For random forest variable importance 
(filter_ranger), variables are sorted by their p-values, and "top_n" will show only the
"top_n" most importance variables (based on p-values).

A toolkit for stratified medicine, subgroup identification, and precision medicine.
Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate
models (counterfactual patient-level quantities, for example the individual treatment effect),
(3) subgroup identification models (find subsets of patients with similar treatment effects),
and (4) parameter estimation and inference (for the overall population and discovered subgroups).
These tools can directly feed into stratified medicine algorithms including PRISM
(patient response identifiers for stratified medicine; Jemielita and Mehrotra (2019)
<arXiv:1912.03337>. PRISM is a flexible and general framework which accepts
user-created models/functions. This package is in beta and will be continually updated.

plot_importance: Importance Plot: Visualize relative importance of variables

Description

Usage

Arguments

Value