| # SVM Ticket Agent Classifier | |
| This model classifies support tickets to either DATA AGENT or USER ACCESS AGENT based on the ticket text. | |
| ## Model Details | |
| - Model Type: Support Vector Machine (SVM) | |
| - Feature Extraction: TF-IDF Vectorizer | |
| - Training Size: 40 samples | |
| - Classes: ['DATA AGENT', 'No decision', 'USER ACCESS AGENT'] | |
| ## Usage | |
| ```python | |
| from joblib import load | |
| # Load model components | |
| pipeline = load('pipeline.joblib') | |
| label_encoder = load('label_encoder.joblib') | |
| # Make prediction | |
| text = "I need access to the sales dashboard" | |
| agent_encoded = pipeline.predict([text])[0] | |
| agent = label_encoder.inverse_transform([agent_encoded])[0] | |
| ``` | |