mPerformance: Performance of predicting a multinomial outcome

In VMTdeJong/mPerformance: Performance measures for multinomial outcome data

Description

Predictive performance for predicted or fitted values. Requires the predicted (or fitted) probability matrix p, and one of the following: labels, indices or indicator.matrix. Preferably one of the former.

Usage

mPerformance(p, labels, indices, indicator.matrix, names = colnames(p),
  na.rm = T)

Arguments

p	An n x K matrix of probabilities, where n is the number of observations, and K the number of mutually exclusive outcome categories.
labels	Vector of length n, containing the labels (character or factor) of the observed outcome categories. If specified, must correspond with the column names of p or with names.
indices	Optional. A vector of length n, containing the indices k, k = 1,...,K, of the observed outcome categories. If specified, these indices must corresond with their respective indices in p.
indicator.matrix	Optional. An n x K matrix indicating the outcome category of each observation, where n is the number of observations, and K the number of mutually exclusive outcome categories. If specified, the order of the columns should correspond with the order of the columns of p.
names	Optional. What are the labels to which the columns of p should be matched? By default, the colnames of the outcome matrix p.
na.rm	logical. Should missing values (including NaN) be removed?

Value

An object of class "mPerformance".A list containing several types of performance measures: discrimination (M-index or multiclass AUC), overall performance (Brier score and various R squares: Cox, Nagelkerke and McFadden) and calibration ().

References

Nagelkerke NJ. A note on a general definition of the coefficient of determination. Biometrika. 1991 Sep 1;78(3):691-2. McFadden D. Conditional logit analysis of qualitative choice behavior.

Brier GW. Verification of forecasts expressed in terms of probability. Monthly weather review. 1950 Jan;78(1):1-3.

Hand DJ, Till RJ. A simple generalisation of the area under the ROC curve for multiple class classification problems. Machine learning. 2001 Nov 1;45(2):171-86.

VMTdeJong/mPerformance documentation built on May 14, 2019, 7:42 a.m.