discrim contains simple bindings to enable the
parsnip package to fit various discriminant analysis models, such as
Here is a simple model using a simulated two-class data set contained in the package:
library(discrim) #> Loading required package: parsnip parabolic_grid <- expand.grid(X1 = seq(-5, 5, length = 100), X2 = seq(-5, 5, length = 100)) fda_mod <- discrim_flexible(num_terms = 3) %>% # increase `num_terms` to find smoother boundaries set_engine("earth") %>% fit(class ~ ., data = parabolic) parabolic_grid$fda <- predict(fda_mod, parabolic_grid, type = "prob")$.pred_Class1 library(ggplot2) ggplot(parabolic, aes(x = X1, y = X2)) + geom_point(aes(col = class), alpha = .5) + geom_contour(data = parabolic_grid, aes(z = fda), col = "black", breaks = .5) + theme_bw() + theme(legend.position = "top") + coord_equal()
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