Data Mining Algorithms In R/Packages/gausspred/assess prediction

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.