evaluate.predictions {SIAMCAT}R Documentation

Evaluate prediction results

Description

This function takes the correct labels and predictions for all samples and evaluates the results using the

as metric. Predictions can be supplied either for a single case or as matrix after resampling of the dataset.

Prediction results are usually produced with the function make.predictions.

Usage

evaluate.predictions(siamcat, verbose = 1)

Arguments

siamcat

object of class siamcat-class

verbose

integer, control output: 0 for no output at all, 1 for only information about progress and success, 2 for normal level of information and 3 for full debug information, defaults to 1

Details

This functions calculates several metrices for the predictions in the pred_matrix-slot of the siamcat-class-object. The Area Under the Receiver Operating Characteristic (ROC) Curve (AU-ROC) and the Precision-Recall Curve will be evaluated and the results will be saved in the eval_data-slot of the supplied siamcat-class-object. The eval_data-slot contains a list with several entries:

For the case of repeated cross-validation, the function will additonally return

Value

object of class siamcat-class with the slot eval_data filled

Examples

data(siamcat_example)

siamcat_evaluated <- evaluate.predictions(siamcat_example)

[Package SIAMCAT version 1.10.0 Index]