predict_GUESS: predict_GUESS
In CalibratR: Mapping ML Scores to Calibrated Predictions

Description Usage Arguments Details Value

returns calibrated predictions for the instances new using the trained GUESS calibration model build_guess_object. Two different evaluation methods are available. Method 1: returns the p-value for the score new under the distribution that is handed over in the build_guess_object Method 2: returns the probability density value for the score new under the distribution that is handed over in the build_guess_object

1 2	predict_GUESS(build_guess_object, new, density_evaluation = 2, return_class_density = FALSE)

`build_guess_object`	output from the `build_GUESS` method
`new`	vector of uncalibrated probabilities
`density_evaluation`	which density evaluation method should be used to infer calculate probabilities, Default: 2
`return_class_density`	if set to TRUE, class densities p(x\|class) are returned, Default: FALSE

dens_case and dens_control are only returned when return_class_density is set to TRUE

a list object containing the following components:

`predictions`	contains a vector of calibrated predictions
`pred_idx`	which density evaluation method was used
`significance_test_set`	the percentage of `new` instances that was evaluated using significant prediction estimates
`dens_case`	a vector containing the p(x\|case) values
`dens_control`	a vector containing the p(x\|control) values