Classifier unlearn #220
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Classifier unlearn #220
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Introduce an `unlearn` method to the classifier, allowing removal of previously learned documents and adjusting internal state accordingly. Include comprehensive test cases to verify functionality under various scenarios, ensuring consistency and error handling in the learning process.
- Add `Remove` method to `SampleUpdater` interface for deleting messages from sample storage. - Update `Detector` to support unlearning of samples upon their removal. - Modify tests to include scenarios for removing messages and verifying probability consistency. - Refactor `SpamFilter` to use new `RemoveHam` and `RemoveSpam` methods in detector. - Ensure message-related operations are executed with proper context and error handling.
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…ples table and cap debug log message length to 1024 characters.
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This is another optimization eliminating the need for a full sample reload on removal and instead applying "unlearn" as a part of the classifier. With this change, the only time a complete reload is needed is on startup.