creditmodel (version 1.3.1)

term_tfidf: 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

# NOT RUN {
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)
# }