train_models_indexical_with_holdout: Train indexical models with cross-validation

In kleinschmidt/phondisttools: Tools for Analyzing Phonetic Cue Distributions

Description

Combines train_test_split, train_models, and list_models to produce a list of indexical groups' models.

Usage

train_models_indexical_with_holdout(d, groups, category, cues,
  holdout = "Talker", ...)

Arguments

d	data frame (a la 'nsp_vows')
groups	quoted name of indexical grouping variable column (e.g., 'Dialect'). One model will be created for each level of this variable.
category	quoted name of column for linguistic category. Each indexical group's model is a list of individual category models
cues	quoted name(s) of column(s) with cue values
holdout	='Talker' unit to perform cross-validation on. one row per level of this variable is created with models trained after removing the corresponding level.
...	additional arguments are passed to train_models

Details

Each group's indexical model is a mixture of models at the linguistic level

Value

the dataframe returned by train_test_split, plus a models list column, each entry of which is a model for one level of groups after holding out that row's Talker (or level of holdout).

kleinschmidt/phondisttools documentation built on May 20, 2019, 5:57 p.m.