classify_indexical_with_holdout: Classify test data with cross-validated models
In kleinschmidt/phondisttools: Tools for Analyzing Phonetic Cue Distributions
Description
Usage
Arguments
Value
View source: R/classification.R
Description
See train_models_indexical_with_holdout.
Usage
1
classify_indexical_with_holdout(data_and_models)
Arguments
data_and_models
output of train_models_indexical_with_holdout, with
one row per talker (or holdout grouping level), and list columns for
data_test and models.
Value
Data frame with one row per combination of data row and model, with
columns corresponding to the held-out and grouping variables, plus model,
lhood (total log-likelihood of data under model), log_posterior, posterior,
and posterior_choice (TRUE for the MAP model and FALSE otherwise)
kleinschmidt/phondisttools documentation built on May 20, 2019, 5:57 p.m.
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Description Usage Arguments Value
View source: R/classification.R
Description
See train_models_indexical_with_holdout.
Usage
1 | classify_indexical_with_holdout(data_and_models)
|
Arguments
data_and_models |
output of train_models_indexical_with_holdout, with
one row per talker (or holdout grouping level), and list columns for
|
Value
Data frame with one row per combination of data row and model, with columns corresponding to the held-out and grouping variables, plus model, lhood (total log-likelihood of data under model), log_posterior, posterior, and posterior_choice (TRUE for the MAP model and FALSE otherwise)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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