Create a Model Specification for Conformal Prediction

Defines how to train a model and generate predictions, allowing any model to be used with conformal prediction methods.

Usage

make_model(train_fun, predict_fun, type = c("regression", "classification"))

Arguments

train_fun

A function with signature function(x, y) that takes a numeric matrix x and response y (numeric for regression, factor for classification) and returns a fitted model object.

predict_fun

A function with signature function(object, x_new) that takes a fitted model object and a numeric matrix x_new and returns predictions. For regression, must return a numeric vector. For classification, must return a probability matrix with columns named by class labels.

type

Character string, either "regression" or "classification".

Value

A predictset_model object (a list with components train_fun, predict_fun, and type).

Examples

reg_model <- make_model(
  train_fun = function(x, y) lm(y ~ ., data = data.frame(y = y, x)),
  predict_fun = function(object, x_new) {
    predict(object, newdata = as.data.frame(x_new))
  },
  type = "regression"
)