aum_line_search_grid {aum}

aum line search grid

Description

Line search for predicted values, with grid search to check.

Usage

aum_line_search_grid(error.diff.df, 
    feature.mat, weight.vec, 
    pred.vec = NULL, 
    maxIterations = nrow(error.diff.df), 
    n.grid = 10L, add.breakpoints = FALSE)

Arguments

error.diff.df

aum_diffs data frame with B rows, one for each breakpoint in example-specific error functions.

feature.mat

N x p matrix of numeric features.

weight.vec

p-vector of numeric linear model coefficients.

pred.vec

N-vector of numeric predicted values. If missing, feature.mat and weight.vec will be used to compute predicted values.

maxIterations

positive int: max number of line search iterations.

n.grid

positive int: number of grid points for checking.

add.breakpoints

add breakpoints from exact search to grid search.

Value

List of class aum_line_search_grid.

Author(s)

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

Examples

if(require("data.table"))setDTthreads(1L)#for CRAN check.

## Example 1: two binary data.
(bin.diffs <- aum::aum_diffs_binary(c(1,0)))
if(requireNamespace("ggplot2"))plot(bin.diffs)
bin.line.search <- aum::aum_line_search_grid(bin.diffs, pred.vec=c(-10,10))
if(requireNamespace("ggplot2"))plot(bin.line.search)

if(requireNamespace("penaltyLearning")){

  ## Example 2: two changepoint examples, one with three breakpoints.
  data(neuroblastomaProcessed, package="penaltyLearning", envir=environment())
  nb.err <- with(neuroblastomaProcessed$errors, data.frame(
    example=paste0(profile.id, ".", chromosome),
    min.lambda,
    max.lambda,
    fp, fn))
  (diffs.subtrain <- aum::aum_diffs_penalty(nb.err, c("4.2", "1.1")))
  if(requireNamespace("ggplot2"))plot(diffs.subtrain)
  (nb.line.search <- aum::aum_line_search_grid(diffs.subtrain, pred.vec=c(-1,1)))
  if(requireNamespace("ggplot2"))plot(nb.line.search)

  ## Example 3: 50 changepoint examples, with linear model.
  X.sc <- scale(neuroblastomaProcessed$feature.mat[1:50,])
  keep <- apply(is.finite(X.sc), 2, all)
  X.subtrain <- X.sc[,keep]
  weight.vec <- rep(0, ncol(X.subtrain))
  diffs.subtrain <- aum::aum_diffs_penalty(nb.err, rownames(X.subtrain))
  nb.weight.search <- aum::aum_line_search_grid(
    diffs.subtrain,
    feature.mat=X.subtrain,
    weight.vec=weight.vec,
    maxIterations = 200)
  if(requireNamespace("ggplot2"))plot(nb.weight.search)

}

## Example 4: counting intersections and intervals at each
## iteration/step size, when there are ties.
(bin.diffs <- aum::aum_diffs_binary(c(0,0,0,1,1,1)))
bin.line.search <- aum::aum_line_search_grid(
  bin.diffs, pred.vec=c(2,3,-1,1,-2,0), n.grid=21) 
if(require("ggplot2")){
  plot(bin.line.search)+
    geom_text(aes(
      step.size, Inf, label=sprintf(
        "%d,%d", intersections, intervals)),
      vjust=1.1,
      data=data.frame(
        panel="threshold", bin.line.search$line_search_result))
}