View source: R/text_analysis.R
classifier_selection_keywords | R Documentation |
classifier_selection_keyword
uses a classifier to select document from keywords.
In 'select' mode the keywords are constructed from the archivesearchresults. In 'eval' mode the keywords are taken from the eval_options and a binary dfm is constructed from the document text. In 'eval_dfm' mode the keywords are taken from the dfm columns, and the eval_classify_var should be a docvar of the dfm.
classifier_selection_keywords( train, archivesearchresults, class_to_keep = 1, training_classify_var = "EV_article", prior = "docfreq", text_field = "ocr", classifier_type = "xgboost", mode = "select", eval_options = list(keywords = c("candidate", "poll", "election", "stone", "riot", "mob", "husting", "disturbance", "rough", "incident"), text_field = "ocr", eval_classify_var = "EV_article", eval_dfm_classifications = "foo") )
train |
the training set of documents |
classifier_type |
The type of classifer to use ("nb" = naive bayes, "xgboost"=xgboost) |
mode |
Should the documents be selected ("select") or the document selection be evaluated from text field("eval"), or evaluated from a dfm ("eval_dfm") (evaluation assumes search results have been classified) |
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