conformal_pvalues {conformalpvalue} | R Documentation |
Conformal P-values Calculation
Description
This function calculates conformal p-values based of binary class labels for test data.
Usage
conformal_pvalues(train_data, calib_data, test_data, target_col, method)
Arguments
train_data |
A data frame containing the training data with the target variable. |
calib_data |
A data frame containing the calibration data with the target variable. |
test_data |
A data frame containing the test data. |
target_col |
The name of the target variable column. |
method |
A character string specifying the classification method to use. Options are 'naiveBayes', 'svm', and 'glm'. This function trains a Naive Bayes classifier, computes non-conformity scores on the calibration data and test data, and calculates conformal p-values of both classes "0" and "1" using the conformal prediction for a binary classification problem. |
Value
A matrix containing p-values for each test case and class.
Examples
# Create dummy train_data, calib_data, and test_data
train_data <- data.frame(
x1 = as.numeric(rnorm(50, 1, 2)),
x2 = as.numeric(rnorm(50, 2.5, 3)),
target = as.factor(rbinom(50, 1, 0.5))
)
calib_data <- data.frame(
x1 = as.numeric(rnorm(50, 1, 2)),
x2 = as.numeric(rnorm(50, 2.5, 3)),
target = as.factor(rbinom(50, 1, 0.5))
)
test_data <- data.frame(
x1 = as.numeric(rnorm(50, 1, 2)),
x2 = as.numeric(rnorm(50, 2.5, 3))
)
p_values <- conformal_pvalues(train_data, calib_data, test_data, target="target", method="svm")
[Package conformalpvalue version 0.1.0 Index]