discrim-package: parsnip methods for discriminant analysis

In tidymodels/discrim: Model Wrappers for Discriminant Analysis

parsnip methods for discriminant analysis

Description

discrim offers various functions to fit classification models via the discriminant analysis.

Details

The model function works with the tidymodels infrastructure so that the model can be resampled, tuned, tided, etc.

Example

As an example, we’ll use a flexible discriminant analysis model of Hastie, Tibshirani, and Buja (1994). This fits a model that uses features generated by the multivariate adaptive regression spline (MARS) model of Friedman (1991). It is able to create class boundaries that are polygons and has built-in feature selection.

The parabolic data from the modeldata package will be used to illustrate:

library(tidymodels)
library(discrim)
tidymodels_prefer()
theme_set(theme_bw())

data(parabolic, package = "modeldata")

To create the model, the discrim_flexible() function is used along with an engine of "earth" (which contains the methods to use the MARS model). We’ll set the number of MARS terms to use but this can be tuned via the methods in the tune package.

The fit() function estimates the model. fit_xy() can be used if one does not wish to use the formula method.

fda_mod <-
  discrim_flexible(num_terms = 3) %>%
  # increase `num_terms` to find smoother boundaries
  set_engine("earth") %>%
  fit(class ~ ., data = parabolic)
fda_mod

## parsnip model object
## 
## Call:
## mda::fda(formula = class ~ ., data = data, method = earth::earth, 
##     nprune = ~3)
## 
## Dimension: 1 
## 
## Percent Between-Group Variance Explained:
##  v1 
## 100 
## 
## Training Misclassification Error: 0.136 ( N = 500 )

Now let’s plot the class boundary by predicting on a grid of points then creating a contour plot for the 50% probability cutoff.

parabolic_grid <-
  expand.grid(X1 = seq(-5, 5, length = 100),
              X2 = seq(-5, 5, length = 100))

parabolic_grid <- 
  parabolic_grid %>% 
  bind_cols(
    predict(fda_mod, parabolic_grid, type = "prob")
  )

ggplot(parabolic, aes(x = X1, y = X2)) +
  geom_point(aes(col = class), alpha = .5) +
  geom_contour(data = parabolic_grid, aes(z = .pred_Class1), col = "black", breaks = .5) +
  coord_equal()

Author(s)

Maintainer: Emil Hvitfeldt [e-mail] (ORCID)

Authors:

• Max Kuhn [e-mail] (ORCID)

Other contributors:

• Posit Software, PBC [copyright holder, funder]

See Also

Useful links:

• https://github.com/tidymodels/discrim

• https://discrim.tidymodels.org/

• Report bugs at https://github.com/tidymodels/discrim/issues

tidymodels/discrim documentation built on April 15, 2024, 9:19 p.m.