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50 lines
2.1 KiB
50 lines
2.1 KiB
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/class_update.R
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\name{class_update}
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\alias{class_update}
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\title{Classifier function for use in combination with the elasticizer function as 'update' parameter (without brackets), see elasticizer documentation for more information}
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\usage{
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class_update(
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out,
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localhost = T,
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model_final,
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varname,
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text,
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words,
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clean,
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ver,
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es_super = .rs.askForPassword("ElasticSearch WRITE"),
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cores = 1
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)
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}
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\arguments{
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\item{out}{Does not need to be defined explicitly! (is already parsed in the elasticizer function)}
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\item{localhost}{Defaults to false. When true, connect to a local Elasticsearch instance on the default port (9200)}
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\item{model_final}{The classification model (e.g. output from textstat_nb(), svm() or others)}
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\item{varname}{String containing the variable name to use for the classification result, usually has the format computerCodes.varname}
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\item{text}{String indicating whether the "merged" field will contain the "full" text, old-style "lemmas" (will be deprecated), new-style "ud", or ud_upos combining lemmas with upos tags}
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\item{words}{String indicating the number of words to keep from each document (maximum document length), 999 indicates the whole document}
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\item{clean}{Boolean indicating whether the results should be cleaned by removing words matching regex (see code).}
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\item{ver}{Short string (preferably a single word/sequence) indicating the version of the updated document (i.e. for a udpipe update this string might be 'udV2')}
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\item{es_super}{Password for write access to ElasticSearch}
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\item{dfm_words}{A dfm containing all the words and only the words used to generate the model (is used for subsetting)}
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}
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\value{
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As this is a nested function used within elasticizer, there is no return output
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}
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\description{
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Classifier function for use in combination with the elasticizer function as 'update' parameter (without brackets), see elasticizer documentation for more information
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}
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\examples{
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class_update(out, localhost = T, model_final, dfm_words, varname, es_super = .rs.askForPassword('ElasticSearch WRITE'))
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}
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