Data Mining Algorithms In R/Packages/gausspred/assess prediction
Description
[edit | edit source]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
[edit | edit source]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
[edit | edit source]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
[edit | edit source]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.