aum {aum}

aum

Description

Compute the Area Under Minimum of False Positives and False Negatives, and its directional derivatives.

Usage

aum(error.diff.df, pred.vec)

Arguments

error.diff.df

data frame of error differences, typically computed via aum_diffs_binary or aum_diffs_penalty. There should be one row for each change in error functions. "example" column indicates example ID (int from 1 to N), "pred" column indicates predicted value where there is a change in the error function(s), "fp_diff" and "fn_diff" columns indicate differences in false positives and false negatives at that predicted value. Note that this representation assumes that each error function has fp=0 at pred=-Inf and fn=0 at pred=Inf.

pred.vec

numeric vector of N predicted values.

Value

Named list of two items: aum is numeric scalar loss value, derivative_mat is N x 2 matrix of directional derivatives (first column is derivative from left, second column is derivative from right). If

Author(s)

Toby Dylan Hocking <[e-mail]> [aut, cre], Jadon Fowler [aut] (Contributed exact line search C++ code)

Examples

(bin.diffs <- aum::aum_diffs_binary(c(0,1)))
aum::aum(bin.diffs, c(-10,10))
aum::aum(bin.diffs, c(0,0))
aum::aum(bin.diffs, c(10,-10))