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Browse files- README.md +25 -0
- label_encoder.joblib +3 -0
- pipeline.joblib +3 -0
README.md
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# SVM Ticket Agent Classifier
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This model classifies support tickets to either DATA AGENT or USER ACCESS AGENT based on the ticket text.
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## Model Details
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- Model Type: Support Vector Machine (SVM)
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- Feature Extraction: TF-IDF Vectorizer
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- Training Size: 40 samples
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- Classes: ['DATA AGENT', 'No decision', 'USER ACCESS AGENT']
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## Usage
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```python
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from joblib import load
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# Load model components
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pipeline = load('pipeline.joblib')
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label_encoder = load('label_encoder.joblib')
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# Make prediction
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text = "I need access to the sales dashboard"
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agent_encoded = pipeline.predict([text])[0]
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agent = label_encoder.inverse_transform([agent_encoded])[0]
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```
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label_encoder.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:4c013e04510ae2858272b2deda8e2f7e21d19185b7cedf9721b0a42c35f1d27b
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size 577
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pipeline.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:bd87f34ee1aa78e4bf3c79e73bdcaa4f1369979167d40d93fde38b20960e31c9
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size 23237
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