Teradata Package for R Function Reference | 17.00 - LDATopicSummary - Teradata Package for R - Look here for syntax, methods and examples for the functions included in the Teradata Package for R.

LDATopicSummary

Description

The LDATopicSummary function displays readable information from the binary model tbl_teradata generated by the Latent Dirichlet Allocation i.e., LDATrainer (td_lda_mle) function.

Usage

  td_lda_topic_summary_mle (
      object = NULL,
      summary = FALSE,
      out.topicwordnum = "all",
      word.weight = FALSE,
      word.count = FALSE,
      out.byword = TRUE,
      object.sequence.column = NULL,
      object.order.column = NULL
  )

Arguments

object	Required Argument. Specifies the model tbl_teradata generated by td_lda_mle. This argument can accept either a tbl_teradata or an object of "td_lda_mle" class.
object.order.column	Optional Argument. Specifies Order By columns for "object". Values to this argument can be provided as vector, if multiple columns are used for ordering. Types: character OR vector of Strings (character)
summary	Optional Argument. Specifies whether to display only a summary of the information in the model tbl_teradata. Default Value: FALSE Types: logical
out.topicwordnum	Optional Argument. Specifies the number of top topic words and their topic identifiers to include in the output tbl_teradata for each training document. The value of "out.topicwordnum" must be either a positive integer in quotes or "all". The value "all" specifies all topic words and their topic identifiers. Types: character
word.weight	Optional Argument. Specifies whether to display the weight (probability of occurrence) of each unique word in each topic. The weights for the unique words in each topic are normalized to 1. Default Value: FALSE Types: logical
word.count	Optional Argument. Specifies whether to display the count (number of occurrences) of each unique word in each topic. Topic distribution is factored into word counts. Default Value: FALSE Types: logical
out.byword	Optional Argument. Specifies whether to display each topic-word pair in its own row. If you specify FALSE, each row contains a unique topic and all words that occur in that topic, separated by commas. Default Value: TRUE Types: logical
object.sequence.column	Optional Argument. Specifies the vector of column(s) that uniquely identifies each row of the input argument "object". The argument is used to ensure deterministic results for functions which produce results that vary from run to run. Types: character OR vector of Strings (character)

Value

Function returns an object of class "td_lda_topic_summary_mle" which is a named list containing object of class "tbl_teradata".
Named list member can be referenced directly with the "$" operator using name: result.

Examples

  
    # Get the current context/connection
    con <- td_get_context()$connection
    
    # Load example data.
    loadExampleData("lda_example","complaints_traintoken")
    
    # Create object(s) of class "tbl_teradata".
    complaints_traintoken <- tbl(con, "complaints_traintoken")
    
    # Example 1 - This example uses the model tbl_teradata generated by td_lda_mle() function 
    # to display only a summary of the information in the model. 
    td_lda_out <- td_lda_mle(data=complaints_traintoken,
                             docid.column='doc_id',
                             word.column='token',
                             topic.num=3,
                             alpha=0.1,
                             eta=0.1,
                             maxiter=50,
                             convergence.delta=0.0001,
                             seed=2,
                             out.topicnum='all',
                             out.topicwordnum='none'
                            )
    td_lda_topic_summary_mle_out <- td_lda_topic_summary_mle(object = td_lda_out,
                                                             summary = TRUE)
    
    # Example 2 - This example displays all topic words and their topic identifiers
    # with each row contains a unique topic and all words that occur in that topic, 
    # separated by commas.
    td_lda_topic_summary_mle_out <- td_lda_topic_summary_mle(object = td_lda_out,
                                                             out.topicwordnum = 'all',
                                                             out.byword = TRUE
                                                             )
    
    # Example 3 - This example displays each topic-word pair with wordweight, wordcount,
    # each topic-word pair in its own row.
    td_lda_topic_summary_mle_out <- td_lda_topic_summary_mle(object = td_lda_out,
                                                             word.weight = TRUE,
                                                             word.count = TRUE,
                                                             out.byword = TRUE
                                                             )