Predict Method for Classification Conformal Objects

Generate prediction sets for new data using a fitted conformal prediction object.

Usage

# S3 method for class 'predictset_class'
predict(object, newdata, ...)

Arguments

object

A predictset_class object.

newdata

A numeric matrix or data frame of new predictor variables.

...

Additional arguments. For Mondrian objects, pass groups_new (a factor or character vector of group labels for each observation in newdata).

Value

A predictset_class object with updated sets and probabilities.

Examples

set.seed(42)
n <- 300
x <- matrix(rnorm(n * 4), ncol = 4)
y <- factor(ifelse(x[,1] > 0, "A", "B"))
x_new <- matrix(rnorm(50 * 4), ncol = 4)

clf <- make_model(
  train_fun = function(x, y) glm(y ~ ., data = data.frame(y = y, x),
                                  family = "binomial"),
  predict_fun = function(object, x_new) {
    df <- as.data.frame(x_new)
    names(df) <- paste0("X", seq_len(ncol(x_new)))
    p <- predict(object, newdata = df, type = "response")
    cbind(A = 1 - p, B = p)
  },
  type = "classification"
)

result <- conformal_lac(x, y, model = clf, x_new = x_new)
#> Warning: glm.fit: algorithm did not converge
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
preds <- predict(result, newdata = matrix(rnorm(5 * 4), ncol = 4))