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Predict writing quality

Source: R/predict_values.R
predict_quality.Rd

Run the specified model(s) on preprocessed data and return predictions. Apply scoring models to ReaderBench, Coh-Metrix, and/or GAMET files. Holistic writing quality can be generated from ReaderBench (model = 'rb_mod3all') or Coh-Metrix files (model = 'coh_mod3all'). Also, Total Words Written, Words Spelled Correctly, Correct Word Sequences, and Correct Minus Incorrect Word Sequences can be generated from a GAMET file (model = 'gamet_cws1').

Usage

predict_quality(model, data)

Arguments

model

A string telling which scoring model to use. Options are: 'rb_mod1', 'rb_mod2', 'rb_mod3narr', 'rb_mod3exp', 'rb_mod3per', or 'rb_mod3all', for ReaderBench files to generate holistic quality, 'coh_mod1', 'coh_mod2', 'coh_mod3narr', 'coh_mod3exp', 'coh_mod3per', or 'coh_mod3all' for Coh-Metrix files to generate holistic quality, and 'gamet_cws1' to generate Total Words Written (TWW), Words Spelled Correctly (WSC), Correct Word Sequences (CWS) and Correct Minus Incorrect Word Sequences (CIWS) scores from a GAMET file.

data

Data frame returned by import_gamet, import_coh, or import_rb.

Value

A data.frame with ID and one column per sub-model prediction. If multiple sub-models are used and all predictions are numeric, an aggregate column named pred_<model>_mean is added (except for "gamet_cws1").

Details

**Offline/examples:** Examples use a built-in 'example' model seeded in a temporary directory via writeAlizer::wa_seed_example_models("example"), so no downloads are attempted and checks stay fast. The temporary files created for the example are cleaned up at the end of the \examples{}.

See also

import_rb, import_coh, import_gamet

Examples

# Offline, CRAN-safe example using a tiny seeded model
if (requireNamespace("withr", quietly = TRUE)) {
  withr::local_options(writeAlizer.offline = TRUE)
  tmp <- withr::local_tempdir()
  withr::local_options(writeAlizer.mock_dir = tmp)

  # Seed the example artifacts into the temp dir and point the loader there
  writeAlizer::wa_seed_example_models("example", dir = tmp)

  coh <- import_coh(system.file("extdata", "sample_coh.csv", package = "writeAlizer"))
  out <- predict_quality("example", coh)
  head(out)
} else {
  # Fallback without 'withr' (still CRAN-safe)
  old <- options(writeAlizer.offline = TRUE)
  on.exit(options(old), add = TRUE)
  ex_dir <- writeAlizer::wa_seed_example_models("example", dir = tempdir())
  old2 <- options(writeAlizer.mock_dir = ex_dir)
  on.exit(options(old2), add = TRUE)

  coh <- import_coh(system.file("extdata", "sample_coh.csv", package = "writeAlizer"))
  out <- predict_quality("example", coh)
  head(out)
}
#>   ID pred_example
#> 1  7          1.5
#> 2  8          1.5
#> 3  9          1.5

# Longer, networked demos
if (FALSE) { # \dontrun{
if (!isTRUE(getOption("writeAlizer.offline", FALSE))) {
  rb <- import_rb(system.file("extdata", "sample_rb.csv", package = "writeAlizer"))
  print(head(predict_quality("rb_mod3all", rb)))

  coh <- import_coh(system.file("extdata", "sample_coh.csv", package = "writeAlizer"))
  print(head(predict_quality("coh_mod3all", coh)))

  gam <- import_gamet(system.file("extdata", "sample_gamet.csv", package = "writeAlizer"))
  print(head(predict_quality("gamet_cws1", gam)))
}
} # }