reinert: Reinert clustering (Rainette)

In nicolarighetti/textools: an R toolbox for text mining tasks

Description

Given a data frame with texts, this function perform Reinert's clustering

Usage

reinert(
  df,
  docid_field = NULL,
  text_field = NULL,
  segment_size = 40,
  k = NULL,
  min_uc_size = 10,
  min_split_members = 5,
  cc_test = 0.3,
  tsj = 3
)

Arguments

df	a data frame with at least a column with textual data and a column with documents' ID
docid_field	name of the column (in quotation marks) containing the IDs of the documents (default NULL)
text_field	name of the column (in quotation marks) containing textual data
min_uc_size	minimum number of forms by document (default 10).
min_split_members	don't try to split groups with fewer members (default 5).
cc_test	contingency coefficient value for feature selection (default 0.3).
tsj	minimum frequency value for feature selection (default 3).
k.max	desired maximum number of clusters (default NULL).

Details

the function is simply a wrapper of functions available in the package rainette. Please refer to the available documentations of rainette

Value

a list containing the result of clustering and the original document term matrix, for subsequent analysis through rainette_explor or rainette_plot

Examples

## Not run: 
reinert_clustering <- reinert(df, docid_field = "URL", text_field = "Message", k = 10)
rainette::rainette_explor(reinert_clustering[[1]], reinert_clustering[[2]])
## End(Not run)

nicolarighetti/textools documentation built on Oct. 16, 2021, 11:20 p.m.