Description Usage Arguments Details Value Author(s) Examples

Build an arbitrary loss matrix for discrete classification

1 2 3 4 | ```
lossMatrix(truthLabels, predLabels, lossValues)
## S3 method for class 'lossMat'
print(x, ...)
``` |

`truthLabels` |
character vector of truth labels |

`predLabels` |
character vector of corresponding predicted labels,
which must be the same length as |

`lossValues` |
numeric vector of corresponding loss values, which must
be the same length as |

`x` |
An object of class |

`...` |
Additional arguments to |

This function checks the inputs and binds the three arguments columnwise into a dataframe.

An object of class `lossMat`

: a dataframe that contains
all the information of the loss matrix to be used by in calculating the loss.

Landon Sego

1 2 3 4 5 6 7 8 9 10 | ```
# A 2x2 symmetric loss matrix
lossMatrix(c("a","a","b","b"), c("a","b","a","b"), c(0, 1, 5, 0))
# A 3x2 asymmetric loss matrix
lossMatrix(rep(letters[1:3], each = 2), rep(letters[4:5], 3),
c(0, 3, 2, 0, 1, 0))
# An unbalanced loss matrix with a missing element.
# Not sure why one would want to do this.
lossMatrix(c("a","a","b"), c("a","b","b"), c(0, 1, 0))
``` |

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