assess_prediction {gausspred}R Documentation

Functions for evaluating predictive probabilities given true values of response of test cases

Description

These functions evaluate predictive probabilities with average minus log probabilities, error rate, and average loss for a defined loss function, or calculate calibration table.

Usage

comp_amlp (probs_pred, responses)
comp_er (probs_pred, responses)
comp_loss (probs_pred, y_true, Mloss)
cal_tab (probs_pred, true_y, ix_y, no_cat=10)

Arguments

probs_pred a matrix of the predictive probabilities, with rows for cases, columns for groups (different values of response).
Mloss a matrix defining a loss function, with rows for true values, and columns for predicted values.
responses, y_true, true_y a vector of true values of response in test cases.
ix_y the index of column used to produce calibration table.
no_cat number of categories in producing calibration table.

Value

comp_amlp returns average minus log probabilities, comp_er returns error rate, comp_loss returns average loss, and expected loss, cal_tab returns a calibration data frame.

See Also

train_pred_gau

Examples

## See train_pred_gau

[Package gausspred version 1.0-0 Index]