R: Predict from a 'ww_area_of

predict.ww_area_of_applicability {waywiser}

R Documentation

Predict from a `ww_area_of_applicability`

Description

Predict from a ww_area_of_applicability

Usage

## S3 method for class 'ww_area_of_applicability'
predict(object, new_data, ...)

Arguments

`object`	A `ww_area_of_applicability` object.
`new_data`	A data frame or matrix of new samples.
`...`	Not used.

Details

The function computes the distance indices of the new data and whether or not they are "inside" the area of applicability.

Value

A tibble of predictions, with two columns: di, numeric, contains the "dissimilarity index" of each point in new_data, while aoa, logical, contains whether a row is inside (TRUE) or outside (FALSE) the area of applicability.

Note that this function is often called using terra::predict(), in which case aoa will be converted to numeric implicitly; 1 values correspond to cells "inside" the area of applicability and 0 corresponds to cells "outside" the AOA.

The number of rows in the tibble is guaranteed to be the same as the number of rows in new_data. Rows with NA predictor values will have NA di and aoa values.

Examples


library(vip)
train <- gen_friedman(1000, seed = 101) # ?vip::gen_friedman
test <- train[701:1000, ]
train <- train[1:700, ]
pp <- stats::ppr(y ~ ., data = train, nterms = 11)
metric_name <- ifelse(
  packageVersion("vip") > package_version("0.3.2"),
  "rsq",
  "rsquared"
)

importance <- vip::vi_permute(
  pp,
  target = "y",
  metric = metric_name,
  pred_wrapper = predict,
  train = train
)

aoa <- ww_area_of_applicability(y ~ ., train, test, importance = importance)
predict(aoa, test)

[Package waywiser version 0.6.0 Index]

Predict from a ww_area_of_applicability