library(cheem)
## Regression setup:
dat <- amesHousing2018_NorthAmes
X <- dat[, 1:9]
Y <- dat$SalePrice
clas <- dat$SubclassMS
## global_view()
ames_rf_chm <- cheem_ls(X, Y, ames_rf_shap, ames_rf_pred, clas,
label = "North Ames, RF, SHAP")
if(interactive()){
global_view(ames_rf_chm, as_ggplot = TRUE) ## early return of ggplot
global_view(ames_rf_chm) ## uses ggplot facets %>% plotly
## Different color mappings, especially for regression
global_view(ames_rf_chm, color = "residual")
global_view(ames_rf_chm, color = "log_maha.data")
global_view(ames_rf_chm, color = "cor_attr_proj.y")
}
## Also consumed by: ?run_app()
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