Build a key from sniglet scores

Each step asks whether the image has one sniglet. method = "balanced" is fordera's algorithm: a sniglet is present when its score is above the quantile of that sniglet's scores over all images; a label has a sniglet if any of its images does; each split uses the unused sniglet that divides the remaining labels most evenly (ties to the earlier one). method = "rpart" suits several images per label. It first gives each sniglet one threshold, the cut of its scores that best separates the labels, and then grows a classification tree on has/lacks, so a sniglet means the same thing wherever the key asks about it.

Usage

keyFromSniglets(
  scores,
  images,
  sniglets,
  method = c("balanced", "rpart"),
  quantile = 0.6,
  desc = "Key generated from sniglets",
  meta = NULL
)

keyFromTerms(scores, images, terms, ...)

Arguments

scores

images x sniglets matrix from snigletScores().

images

imageSet() data frame with one row per row of scores.

sniglets

The discoverSniglets() object the scores were computed with. Names given with renameSniglets() are used in the key.

method

"balanced" or "rpart".

quantile

Presence threshold quantile for "balanced".

desc, meta

Title and metadata of the key.

terms, ...

keyFromTerms() is the earlier name of keyFromSniglets(); its third argument was called terms.

Value

A dimoose key whose leads carry Feature, Test, Threshold and Question, and whose features table holds the centroids. Feature ids are "sniglet:<coined word>" and never change; label is the name shown, which renameSniglets() changes.

Both leads describe something

A lead that only says a specimen lacks something gives the reader nothing to look for. Where it can, the "Lacks" lead therefore also names what its images have instead: another sniglet that at least 90% of them have and at most 10% of the other side do ("Lacks gaithiark; has blienvaurk"). The machine still tests only the first sniglet. Every lead also records example regions from the images that take it (Examples), which patchExemplars() turns into crops: for a "Lacks" lead with no such second sniglet, they are the regions that come closest to the missing one.