SOL-C01 · Question #203
A data analyst is using Snowflake Cortex's CLASSIFY TEXT function to categorize customer feedback. They notice that some feedback containing sarcasm is consistently misclassified. Which of the followi
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Question
A data analyst is using Snowflake Cortex's CLASSIFY TEXT function to categorize customer feedback. They notice that some feedback containing sarcasm is consistently misclassified. Which of the following strategies would be MOST effective in improving the accuracy of CLASSIFY TEXT in this scenario, considering the function's limitations and capabilities?
Options
- AManually create a custom classification model within Snowflake using Python User-Defined
- BPreprocess the customer feedback using a sentiment analysis UDF that identifies and flags
- CThere is no way to improve the accuracy of CLASSIFY _ TEXT. Its performance is fixed and
- DSince CLASSIFY TEXT is a black-box function, the only way to improve performance is to provide
- ESubmit a feature request to Snowflake support requesting they improve the CLASSIFY TEXT
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