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').
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, orimport_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{}.
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 (skipped on CRAN)
# \donttest{
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)))
}
#> ℹ Downloaded model artifact:
#> * File: rb_exp_vars_v2.rds
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: rb_narr_vars_v2.rds
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: rb_per_vars_v2.rds
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> Warning: These variables have zero variances: RB.SenAllit, RB.AvgDepsBl_csubj, RB.AvgDepsBl_iobj
#> Warning: These variables have zero variances: RB.AvgConnBl_complex_subordinators, RB.SenAllit, RB.AvgDepsBl_csubj, RB.AvgDepsBl_iobj, RB.AvgDepsSen_iobj
#> Warning: These variables have zero variances: RB.AvgConnBl_complex_subordinators, RB.SenAllit, RB.AvgDepsBl_csubj, RB.AvgDepsSen_csubj, RB.AvgDepsBl_iobj
#> ℹ Downloaded model artifact:
#> * File: rb_mod3exp_v2.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: rb_mod3narr_v2.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: rb_mod3per_v2.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ID pred_rb_mod3exp pred_rb_mod3narr pred_rb_mod3per pred_rb_mod3all_mean
#> 1 7 -1.4434553 -1.69349246 -0.9573641 -1.36477065
#> 2 8 0.0796015 -0.03163491 -0.2293523 -0.06046189
#> 3 9 1.4068790 1.80142661 1.3995404 1.53594866
#> ℹ Downloaded model artifact:
#> * File: coh_exp_vars.rds
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: coh_narr_vars.rds
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: coh_per_vars.rds
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> Warning: These variables have zero variances: WRDPRP1p
#> Warning: These variables have zero variances: WRDPRP1p
#> Warning: These variables have zero variances: WRDPRP1p
#> ℹ Downloaded model artifact:
#> * File: coh_mod3exp.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: coh_mod3narr.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: coh_mod3per.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ID pred_coh_mod3exp pred_coh_mod3narr pred_coh_mod3per pred_coh_mod3all_mean
#> 1 7 -2.5052929 -3.496357 -2.9239837 -2.9752112
#> 2 8 0.5765171 1.436159 0.6002912 0.8709891
#> 3 9 1.6753017 2.488845 3.3214388 2.4951951
#> ℹ Downloaded model artifact:
#> * File: CWS_mod1a.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ℹ Downloaded model artifact:
#> * File: CIWS_mod1a.rda
#> * Cache: /home/runner/.cache/R/writeAlizer
#> (Artifacts are downloaded only the first time you use a model.)
#> Tip: clear the cache with wa_cache_clear() if needed.
#> ID pred_TWW_gamet pred_WSC_gamet pred_CWS_mod1a pred_CIWS_mod1a
#> 1 7 135 129 125.8289 107.8254
#> 2 8 171 168 157.8647 141.8125
#> 3 9 191 189 168.2293 149.5521
# }