Predict using TabPFN

Predict using TabPFN

Usage

# S3 method for class 'tab_pfn'
predict(object, new_data, ...)

# S3 method for class 'tab_pfn'
augment(x, new_data, ...)

Arguments

object, x

A tab_pfn object.

new_data

A data frame or matrix of new predictors.

...

Not used, but required for extensibility.

Value

predict() returns a tibble of predictions and augment() appends the columns in new_data. In either case, the number of rows in the tibble is guaranteed to be the same as the number of rows in new_data.

For regression data, the prediction is in the column .pred. For classification, the class predictions are in .pred_class and the probability estimates are in columns with the pattern .pred_{level} where level is the levels of the outcome factor vector.

Examples

# Minimal example for quick execution
car_train <- mtcars[ 1:5,   ]
car_test  <- mtcars[10:15, -1]

# Fit
if (is_tab_pfn_installed() & interactive()) {
 mod <- tab_pfn(mpg ~ cyl + log(drat), car_train)

 # Predict
 predict(mod, car_test)
 augment(mod, car_test)
}