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33 lines
2.0 KiB
33 lines
2.0 KiB
#' 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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#' 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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#' @param out Does not need to be defined explicitly! (is already parsed in the elasticizer function)
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#' @param model_final The classification model (e.g. output from textstat_nb(), svm() or others)
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#' @param 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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#' @param varname String containing the variable name to use for the classification result, usually has the format computerCodes.varname
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#' @param es_super Password for write access to ElasticSearch
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#' @return As this is a nested function used within elasticizer, there is no return output
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#' @export
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#' @examples
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#' elasticizer(query, src = T, es_pwd = es_pwd, update = class_update, model_final = model_final, dfm_words = dfm_words, varname = computerCodes.varname, es_super = es_super)
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#################################################################################################
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#################################### Update any kind of classification ##########################
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#################################################################################################
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class_update <- function(out, model_final, dfm_words, varname, es_super) {
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print('updating')
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dfm <- dfm_gen(out, text = 'lemmas') %>%
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dfm_keep(dfm_words, valuetype="fixed", verbose=T)
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pred <- data.frame(id = out$`_id`, pred = predict(model_final, newdata = dfm))
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bulk <- apply(pred, 1, bulk_writer, varname = varname)
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res <- elastic_update(bulk, es_super = es_super)
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stop_for_status(res)
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content(res, "parsed", "application/json")
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appData <- content(res)
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if (appData$errors == T){
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print(appData)
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stop("Aborting, errors found during updating")
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}
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print("updated")
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Sys.sleep(1)
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}
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