This example uses the model file sentimentmodel1.bin, output by the SentimentTrainer Example.
Input
- Input table: sentiment_extract_input, as in SentimentExtractor Example: InputModelFile ('dictionary'), AnalysisType ('document')
SQL Call
SELECT * FROM SentimentEvaluator ( ON SentimentExtractor ( ON sentiment_extract_input USING TextColumn ('review') Accumulate ('category') InputModelFile ('classification:sentimentmodel1.bin') ) PARTITION BY 1 USING ObservationColumn ('category') SentimentColumn ('out_polarity') ) AS dt;
Output
evaluation_result ---------------------------------------------------------------------------------- positive record (total relevant, relevant, total retrieved): 5 5 5 recall and precision: 1.00 1.00 negative record (total relevant, relevant, total retrieved): 5 5 5 recall and precision: 1.00 1.00 positive and negative record (total relevant, relevant, total retrieved): 10 10 10 recall and precision: 1.00 1.00
Download a zip file of all examples and a SQL script file that creates their input tables.