SentimentEvaluator Example: Dictionary Table Instead of Model File - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.10
1.1
Published
October 2019
Language
English (United States)
Last Update
2019-12-31
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ima1540829771750.ditamap
dita:ditavalPath
jsj1481748799576.ditaval
dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

This example uses a dictionary table, sentiment_word, instead of a model file. See sentiment_word in SentimentExtractor Example: Dictionary Table Instead of Model File.

SQL Call

SELECT * FROM SentimentEvaluator (
  ON SentimentExtractor (
    ON sentiment_extract_input PARTITION BY ANY
    ON sentiment_word AS dict DIMENSION
    USING
    TextColumn ('review')
    Accumulate ('category')
  ) PARTITION BY 1
  USING
  ObservationColumn ('category')
  SentimentColumn ('out_polarity')
) AS dt;

Output

 evaluation_result                                                                
 -------------------------------------------------------------------------------- 
 positive record (total relevant, relevant, total retrieved): 5 5 6              
 recall and precision: 1.00 0.83                                                 
 negative record (total relevant, relevant, total retrieved): 5 3 3              
 recall and precision: 0.60 1.00                                                 
 positive and negative record (total relevant, relevant, total retrieved): 10 8 9
 recall and precision: 0.80 0.89

Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.