Description Usage Arguments Value See Also Examples

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

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

`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 |

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)
``` |

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