SentimentEvaluator Output - Teradata Vantage

Machine Learning Engine Analytic Function Reference
Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
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rnn1580259159235.ditamap
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantage™

Output Message Schema

Column Data Type Description
evaluation_result VARCHAR Reports these values:
  • Positive record (total relevant, relevant, total retrieved)
  • Recall and precision
  • Negative record (total relevant, relevant, total retrieved)
  • Recall and precision
  • Positive and negative record (total relevant, relevant, total retrieved)
  • Recall and precision

Calculation of Precision and Recall

Term Definitions
Term Definition
POS_EXPECT Count of rows in which observed sentiment is POS.
POS_RETURN Count of rows in which actual sentiment is POS.
POS_TRUE Count of rows in which both observed and actual sentiment are POS.
NEG_EXPECT Count of rows in which observed sentiment is NEG.
NEG_RETURN Count of rows in which actual sentiment is NEG.
NEG_TRUE Count of rows in which both observed and actual sentiment are NEG.
NEU_EXPECT Count of rows in which observed sentiment is NEU.
NEU_RETURN Count of rows in which actual sentiment is NEU.
NEU_TRUE Count of rows in which both observed and actual sentiment are NEU.
Calculations
Sentiment Precision Recall
Positive POS_TRUE / POS_RETURN POS_TRUE / POS_EXPECT
Negative NEG_TRUE / NEG_RETURN NEG_TRUE / NEG_EXPECT
Neutral NEU_TRUE / NEU_RETURN NEU_TRUE / NEU_EXPECT
All (POS_TRUE + NEG_TRUE + NEU_TRUE) / (POS_RETURN + NEG_RETURN + NEU_RETURN) (POS_TRUE + NEG_TRUE + NEU_TRUE) / (POS_EXPECT + NEG_EXPECT + NEU_EXPECT)