Column Name | Data Type | Description |
---|---|---|
evaluation_result | VARCHAR | Reports these values:
|
Given these definitions:
- 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
Precision and recall are calculated as follows:
- Positive sentiment:
- Precision = POS_TRUE / POS_RETURN
- Recall = POS_TRUE / POS_EXPECT
- Negative sentiment:
- Precision = NEG_TRUE / NEG_RETURN
- Recall = NEG_TRUE / NEG_EXPECT
- Neutral sentiment:
- Precision = NEU_TRUE / NEU_RETURN
- Recall = NEU_TRUE / NEU_EXPECT
- All sentiment:
- Precision = (POS_TRUE + NEG_TRUE + NEU_TRUE) / (POS_RETURN + NEG_RETURN + NEU_RETURN)
- Recall = (POS_TRUE + NEG_TRUE + NEU_TRUE) / (POS_EXPECT + NEG_EXPECT + NEU_EXPECT)