| term_tfidf {creditmodel} | R Documentation | 
TF-IDF
Description
The term_filter is for filtering stop_words and low frequency words.
The term_idf is for computing idf(inverse documents frequency) of terms.
The term_tfidf is for computing tf-idf of documents.
Usage
term_tfidf(term_df, idf = NULL)
term_idf(term_df, n_total = NULL)
term_filter(term_df, low_freq = 0.01, stop_words = NULL)
Arguments
term_df | 
 A data.frame with id and term.  | 
idf | 
 A data.frame with idf.  | 
n_total | 
 Number of documents.  | 
low_freq | 
 Use rate of terms or use numbers of terms.  | 
stop_words | 
 Stop words.  | 
Value
A data.frame
Examples
term_df = data.frame(id = c(1,1,1,2,2,3,3,3,4,4,4,4,4,5,5,6,7,7,
                            8,8,8,9,9,9,10,10,11,11,11,11,11,11),
terms = c('a','b','c','a','c','d','d','a','b','c','a','c','d','a','c',
          'd','a','e','f','b','c','f','b','c','h','h','i','c','d','g','k','k'))
term_df = term_filter(term_df = term_df, low_freq = 1)
idf = term_idf(term_df)
tf_idf = term_tfidf(term_df,idf = idf)
[Package creditmodel version 1.3.1 Index]