twitter-stock-sentiment
mixed-naive-bayes
| twitter-stock-sentiment | mixed-naive-bayes | |
|---|---|---|
| 1 | 1 | |
| 9 | 63 | |
| - | - | |
| 0.0 | 2.5 | |
| about 3 years ago | about 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
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twitter-stock-sentiment
mixed-naive-bayes
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[Discussion] Unique uses of recommendation systems?
Some of the features are categorical, such as request type (is it about troubleshoot, price request, etc.), product, language, SLA, etc.; and some are continuous, namely an embedding vector generated from the ticket free form text. Then we use this library that allows the training of a Naive Bayes model using mixed type of features (categorical and continuous).
What are some alternatives?
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