# risk_calculate: Risk Calculate In abcrlda: Asymptotically Bias-Corrected Regularized Linear Discriminant Analysis

## Description

Estimates risk and error by applying a constructed classifier (an object of class abcrlda) to a given set of observations.

## Usage

 `1` ```risk_calculate(object, x_true, y_true) ```

## Arguments

 `object` An object of class "abcrlda". `x_true` Matrix of values for x for which true class labels are known. `y_true` A numeric vector or factor of true class labels. Factor should have either two levels or be a vector with two distinct values. If `y_true` is presented as a vector, it will be coerced into a factor. Length of `y_true` has to correspond to number of samples in `x_test`.

## Value

A list of parameters where

 `actual_err0` Error rate for class 0. `actual_err1` Error rate for class 1. `actual_errTotal` Error rate overall. `actual_normrisk` Risk value normilized to be between 0 and 1. `actual_risk` Risk value without normilization.

Other functions in the package: `abcrlda()`, `cross_validation()`, `da_risk_estimator()`, `grid_search()`, `predict.abcrlda()`
 ```1 2 3 4 5 6 7``` ```data(iris) train_data <- iris[which(iris[, ncol(iris)] == "virginica" | iris[, ncol(iris)] == "versicolor"), 1:4] train_label <- factor(iris[which(iris[, ncol(iris)] == "virginica" | iris[, ncol(iris)] == "versicolor"), 5]) model <- abcrlda(train_data, train_label, gamma = 0.5, cost = 0.75) risk_calculate(model, train_data, train_label) ```